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diff --git a/README.md b/README.md
index 7da79263d0e701a53a0d662d245c4fc3db39b287..d2ff39e70e358164c04eb3557d4e3eda093c250e 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,46 @@
----
-license: cc-by-4.0
----
+# SenseBench — Representative Sample (1,000 instances)
+
+This is a representative sample of the [SenseBench](https://huggingface.co/datasets/Zhongchenchen/SenseBench) dataset, created for NeurIPS 2026 reviewer inspection.
+
+## Sampling Method
+
+- **Strategy**: Stratified random sampling proportional to the joint distribution of (task_category, image_count)
+- **Random seed**: 42 (fully reproducible)
+- **Tool**: `sample.py` in this directory
+
+### Original Distribution (10,815 total)
+
+| Category | Single | Paired | Total |
+|----------|--------|--------|-------|
+| Perception | 6,700 (62.0%) | 2,915 (27.0%) | 9,615 |
+| Description | 600 (5.5%) | 600 (5.5%) | 1,200 |
+
+### Sampled Distribution (1,000 total)
+
+| Category | Single | Paired | Total |
+|----------|--------|--------|-------|
+| Perception | 620 (62.0%) | 270 (27.0%) | 890 |
+| Description | 55 (5.5%) | 55 (5.5%) | 110 |
+
+## Contents
+
+```
+seleted/
+├── sample.py              # Sampling script (seed=42, reproducible)
+├── questions.jsonl        # 1,000 sampled instances
+├── README.md              # This file
+├── Perception/
+│   ├── single/            # 620 images (289 MB)
+│   └── paired/            # 540 images (165 MB)
+└── Description/
+    ├── single/            #  55 images (23 MB)
+    └── paired/            # 110 images (34 MB)
+```
+
+Total: ~511 MB
+
+## Reproduce
+
+```bash
+python sample.py
+```
diff --git a/questions.jsonl b/questions.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..cb333273351bf3b10cfaf6e309c928ae00a786ad
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+{"id": "985fafe4-6530-46f9-b92a-01a56392d93b", "images": ["Perception/single/985fafe4-6530-46f9-b92a-01a56392d93b_0.png"], "question": "What form of distortion is most apparent here?\nA.No distortion\nB.haze\nC.blur\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "c9b9c3ba-ad52-4548-827c-4e4beebb22c3", "images": ["Description/single/c9b9c3ba-ad52-4548-827c-4e4beebb22c3_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe stripe noise introduces horizontal bands across the image, disrupting the uniformity of colors and textures and creating a visually chaotic appearance. The distortion obscures fine details, making it difficult to discern building edges, road layouts, and vegetation patterns accurately. The image quality is poor, significantly impairing its usability for analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "1d9b420e-76e3-418c-a7ac-671446415d06", "images": ["Perception/single/1d9b420e-76e3-418c-a7ac-671446415d06_0.png"], "question": "What visual defect does this image exhibit?\nA.blur\nB.No distortion\nC.color distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "d431e7dd-dfe1-4e62-9fb5-999609057092", "images": ["Perception/single/d431e7dd-dfe1-4e62-9fb5-999609057092_0.png"], "question": "Is sidelobe interference visible in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "81892219-68e2-43ee-9a6f-eae11b806cf8", "images": ["Perception/single/81892219-68e2-43ee-9a6f-eae11b806cf8_0.png"], "question": "Which distortion most significantly affects this image?\nA.No distortion\nB.color distortion\nC.image stretching\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "70dfa822-a634-4aca-b601-faf24fd88b3f", "images": ["Perception/paired/70dfa822-a634-4aca-b601-faf24fd88b3f_0.png", "Perception/paired/70dfa822-a634-4aca-b601-faf24fd88b3f_1.png"], "question": "What is the severity of the artifact in Image 2 when compared to Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "e08dc00c-db54-4098-8445-3947c3a8732b", "images": ["Perception/single/e08dc00c-db54-4098-8445-3947c3a8732b_0.png"], "question": "Is gaussian blur a critical issue in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "820f45ac-e701-4fea-ad5a-0e9373a4c10f", "images": ["Perception/single/820f45ac-e701-4fea-ad5a-0e9373a4c10f_0.png"], "question": "Identify the main type of corruption in this image.\nA.noise\nB.cloud\nC.missing tiles\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "acc003af-8491-4329-a928-3a8072c4cf0b", "images": ["Perception/paired/acc003af-8491-4329-a928-3a8072c4cf0b_0.png", "Perception/paired/acc003af-8491-4329-a928-3a8072c4cf0b_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.cloud\nB.image compression\nC.image stretching\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "8ee73e96-d045-41ee-ad82-9f14a6c3c63b", "images": ["Perception/single/8ee73e96-d045-41ee-ad82-9f14a6c3c63b_0.png"], "question": "What visual defect does this image exhibit?\nA.blur\nB.missing tiles\nC.haze\nD.dead pixel", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "2566a3a3-3161-4bc2-aaa9-a98403fa1a72", "images": ["Perception/paired/2566a3a3-3161-4bc2-aaa9-a98403fa1a72_0.png", "Perception/paired/2566a3a3-3161-4bc2-aaa9-a98403fa1a72_1.png"], "question": "Comparing Image 1 (reference) and Image 2 (degraded), what distortion best explains the difference?\nA.image stretching\nB.image compression\nC.noise\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "861206b7-fd58-4031-8e14-d88e6b7bc800", "images": ["Perception/single/861206b7-fd58-4031-8e14-d88e6b7bc800_0.png"], "question": "Is image compression a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "7c069ec7-e7c1-44d2-9304-3e297a9ea5a8", "images": ["Perception/paired/7c069ec7-e7c1-44d2-9304-3e297a9ea5a8_0.png", "Perception/paired/7c069ec7-e7c1-44d2-9304-3e297a9ea5a8_1.png"], "question": "How would you grade the distortion intensity affecting Image 2 relative to its reference counterpart?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b428261f-9143-4ac6-85c6-6b30c7072246", "images": ["Perception/single/b428261f-9143-4ac6-85c6-6b30c7072246_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "6a25014a-da08-4632-84e8-0b53fbcf62eb", "images": ["Perception/paired/6a25014a-da08-4632-84e8-0b53fbcf62eb_0.png", "Perception/paired/6a25014a-da08-4632-84e8-0b53fbcf62eb_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "b4914e74-4441-414f-a66c-908cd89061c7", "images": ["Description/single/b4914e74-4441-414f-a66c-908cd89061c7_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe impulse noise introduces random bright and dark speckles across the image, obscuring details and creating a grainy appearance. Key features such as building edges, road boundaries, and vegetation patterns are heavily disrupted, making it difficult to discern structural or spatial information. The image quality is poor, significantly limiting its usability for interpretation or analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "d4480370-5c21-4adb-b2e0-dcb06c58d21d", "images": ["Perception/single/d4480370-5c21-4adb-b2e0-dcb06c58d21d_0.png"], "question": "What category of distortion does this image belong to?\nA.image compression\nB.color distortion\nC.cloud\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "f800f90f-2e77-454c-9fba-7cd3bf34e2e3", "images": ["Perception/single/f800f90f-2e77-454c-9fba-7cd3bf34e2e3_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.dead pixel\nB.color distortion\nC.image compression\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "1963e269-1bc5-448f-93ae-113c0884e8f5", "images": ["Perception/single/1963e269-1bc5-448f-93ae-113c0884e8f5_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "e3575f0e-894f-4e7a-9db7-2d8baba83d15", "images": ["Perception/single/e3575f0e-894f-4e7a-9db7-2d8baba83d15_0.png"], "question": "Identify the main type of corruption in this image.\nA.noise\nB.cloud\nC.blur\nD.missing tiles", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "4ef77699-4153-428d-ba28-9ca6bd0bc604", "images": ["Description/paired/4ef77699-4153-428d-ba28-9ca6bd0bc604_0.png", "Description/paired/4ef77699-4153-428d-ba28-9ca6bd0bc604_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains severe cloud artifacts, with a large, bright white area in the center and additional cloud cover obscuring significant portions of the landscape. Image 2 has no observable distortions and presents a clear, high-quality view of the terrain. Therefore, Image 2 has higher overall quality due to the absence of any visual obstructions or distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "77955858-cb57-4c11-94ae-01ecc06964f2", "images": ["Perception/single/77955858-cb57-4c11-94ae-01ecc06964f2_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "3ff9f3bb-45e0-4c7d-a622-1512d1d02566", "images": ["Perception/paired/3ff9f3bb-45e0-4c7d-a622-1512d1d02566_0.png", "Perception/paired/3ff9f3bb-45e0-4c7d-a622-1512d1d02566_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "888582fe-84e6-4127-9ae8-3878aec8a595", "images": ["Perception/paired/888582fe-84e6-4127-9ae8-3878aec8a595_0.png", "Perception/paired/888582fe-84e6-4127-9ae8-3878aec8a595_1.png"], "question": "Which distortion most clearly appears in the degraded image?\nA.missing tiles\nB.color distortion\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "93f5b8fb-bd3a-4732-a1db-f8f9e7833938", "images": ["Perception/single/93f5b8fb-bd3a-4732-a1db-f8f9e7833938_0.png"], "question": "Do visual cues of haze and image compression appear in the image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "6949e3f5-6620-4067-8f6f-8859f8294897", "images": ["Perception/paired/6949e3f5-6620-4067-8f6f-8859f8294897_0.png", "Perception/paired/6949e3f5-6620-4067-8f6f-8859f8294897_1.png"], "question": "Given that Image 1 is the reference and Image 2 is distorted, how severe is the degradation in Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "dd3f4897-82a0-430f-aef6-1daf99301299", "images": ["Perception/paired/dd3f4897-82a0-430f-aef6-1daf99301299_0.png", "Perception/paired/dd3f4897-82a0-430f-aef6-1daf99301299_1.png"], "question": "Which distortion label best fits the difference between these paired images?\nA.cloud\nB.color distortion\nC.noise\nD.haze", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "f0851991-37a3-4422-94fb-8dae79f8cebe", "images": ["Perception/single/f0851991-37a3-4422-94fb-8dae79f8cebe_0.png"], "question": "Does stripe noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "c673cd30-b17c-424b-b92b-2961dadff14a", "images": ["Description/single/c673cd30-b17c-424b-b92b-2961dadff14a_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe horizontal lines disrupt the visual continuity, creating a fragmented appearance across the image. These distortions obscure fine details, such as road markings and building structures, making it difficult to interpret spatial features accurately. The image quality is poor due to the pronounced interference caused by the dead pixel distortion.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "5e0b5c20-470a-4838-be8f-674fe1457f91", "images": ["Perception/single/5e0b5c20-470a-4838-be8f-674fe1457f91_0.png"], "question": "Can gaussian noise be observed in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "5914e128-6229-47ca-9f22-62fe25d56bd0", "images": ["Perception/paired/5914e128-6229-47ca-9f22-62fe25d56bd0_0.png", "Perception/paired/5914e128-6229-47ca-9f22-62fe25d56bd0_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.haze\nB.blur\nC.No distortion\nD.dead pixel", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "15addda5-4bf9-4c8c-98a3-862fea7e5396", "images": ["Perception/single/15addda5-4bf9-4c8c-98a3-862fea7e5396_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.sidelobe\nC.striping\nD.ghosting", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "bcd61ac4-93d6-4c9f-8afd-6a477f7b762b", "images": ["Perception/single/bcd61ac4-93d6-4c9f-8afd-6a477f7b762b_0.jpg"], "question": "Does speckle noise compromise the data integrity?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "86a8f7ce-b236-41b9-a482-79735c0d1b62", "images": ["Perception/single/86a8f7ce-b236-41b9-a482-79735c0d1b62_0.png"], "question": "Which of the following distortions are present in this image? (Select all that apply)\nA. motion blur\nB. deadline noise\nC. image compression\nD. image stretching", "answer": "A,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "f242decf-ae9d-4c85-b27a-101ba00c87a3", "images": ["Perception/single/f242decf-ae9d-4c85-b27a-101ba00c87a3_0.png"], "question": "Identify the main type of corruption in this image.\nA.No distortion\nB.color distortion\nC.noise\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "d289b75e-48b1-4247-8db5-1c4528ed3256", "images": ["Description/paired/d289b75e-48b1-4247-8db5-1c4528ed3256_0.png", "Description/paired/d289b75e-48b1-4247-8db5-1c4528ed3256_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 contains moderate image stretching artifacts, which manifest as elongated and distorted features, particularly noticeable in the terrain and geological formations. Image 1 has higher overall quality because it lacks the stretching distortions present in Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "e81fa63b-5b3c-40b8-9a0d-e9839bfbe1b7", "images": ["Perception/paired/e81fa63b-5b3c-40b8-9a0d-e9839bfbe1b7_0.png", "Perception/paired/e81fa63b-5b3c-40b8-9a0d-e9839bfbe1b7_1.png"], "question": "Does deadline noise interfere with interpretation of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "4fd98669-46b3-4e73-9d45-28d2803eab38", "images": ["Perception/single/4fd98669-46b3-4e73-9d45-28d2803eab38_0.png"], "question": "Does the image exhibit image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "b94511f3-b0ac-4311-bc27-8882f44990cc", "images": ["Description/single/b94511f3-b0ac-4311-bc27-8882f44990cc_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe haze causes significant blurring and desaturation, making terrain features appear faint and indistinct.  \nRoads and pathways lose clarity, and vegetation patterns are obscured, reducing the ability to discern land use or structural details.  \nThe image quality is poor, with limited utility for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "ec8b6139-5d12-4f28-857e-18a13fbbc110", "images": ["Description/single/ec8b6139-5d12-4f28-857e-18a13fbbc110_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces blocky artifacts and reduces fine details, making the terrain appear unnaturally pixelated and fragmented. The loss of texture and clarity obscures geological features, making it difficult to discern subtle variations in the landscape. The image quality is poor, significantly hindering its usability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "b9870be2-c8b1-4519-9d59-5ed7846e7738", "images": ["Perception/single/b9870be2-c8b1-4519-9d59-5ed7846e7738_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "72c03d90-08ec-49a9-ad61-b082c4ed9486", "images": ["Perception/single/72c03d90-08ec-49a9-ad61-b082c4ed9486_0.png"], "question": "Identify the main type of corruption in this image.\nA.noise\nB.cloud\nC.missing tiles\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "3500233e-2ac3-4c20-b215-d064e41bd45c", "images": ["Perception/single/3500233e-2ac3-4c20-b215-d064e41bd45c_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "388b730d-9866-40aa-8a5b-9724c7dfb389", "images": ["Perception/paired/388b730d-9866-40aa-8a5b-9724c7dfb389_0.png", "Perception/paired/388b730d-9866-40aa-8a5b-9724c7dfb389_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e7ec0179-f1b5-43f5-adda-7aabc099b49d", "images": ["Description/paired/e7ec0179-f1b5-43f5-adda-7aabc099b49d_0.png", "Description/paired/e7ec0179-f1b5-43f5-adda-7aabc099b49d_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits moderate spatially correlated noise artifacts, which manifest as grainy and uneven textures across the image, reducing its clarity. Image 2 shows no observable distortions and maintains a clear and consistent visual quality throughout. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior clarity compared to Image 1.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "f577ab60-5c3f-4939-bb52-d4920bd5e282", "images": ["Perception/single/f577ab60-5c3f-4939-bb52-d4920bd5e282_0.png"], "question": "Identify the main type of corruption in this image.\nA.haze\nB.noise\nC.dead pixel\nD.No distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "38726044-c971-4ff6-aa6d-e5cafb251c42", "images": ["Perception/single/38726044-c971-4ff6-aa6d-e5cafb251c42_0.png"], "question": "What is the main cause of degradation in this image?\nA.noise\nB.haze\nC.cloud\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "8bb8f199-4c9f-4a1c-b6c1-5d311955d3bd", "images": ["Description/paired/8bb8f199-4c9f-4a1c-b6c1-5d311955d3bd_0.png", "Description/paired/8bb8f199-4c9f-4a1c-b6c1-5d311955d3bd_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 contains severe cloud artifacts, with a large, bright, and opaque cloud covering the central portion of the image, obscuring significant details. Therefore, Image 1 has higher overall quality due to the absence of any distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "195c3fd5-4095-4225-b5f0-45ae2e133cd4", "images": ["Perception/single/195c3fd5-4095-4225-b5f0-45ae2e133cd4_0.png"], "question": "Does image compression result in missing information?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "3287b17c-b8be-4fae-8ab6-423084622361", "images": ["Perception/single/3287b17c-b8be-4fae-8ab6-423084622361_0.png"], "question": "Does image compression affect the image quality?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "310349a4-8ee8-4c3e-869a-c8e4a6acd673", "images": ["Perception/single/310349a4-8ee8-4c3e-869a-c8e4a6acd673_0.png"], "question": "Which distortion most significantly affects this image?\nA.haze\nB.noise\nC.image stretching\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "4f73e8f3-8669-4c0d-8d43-f46b57506cab", "images": ["Perception/single/4f73e8f3-8669-4c0d-8d43-f46b57506cab_0.png"], "question": "Is sidelobe interference a critical issue in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "095661c4-f71c-413b-a818-10892b776f07", "images": ["Perception/single/095661c4-f71c-413b-a818-10892b776f07_0.png"], "question": "What is the main cause of degradation in this image?\nA.image compression\nB.color distortion\nC.noise\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "836c2bfc-6793-45fb-95e8-38f0f99459d5", "images": ["Perception/single/836c2bfc-6793-45fb-95e8-38f0f99459d5_0.png"], "question": "Does the image exhibit image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "dc67ab7d-81e6-4321-a398-c5a74ea773fd", "images": ["Perception/single/dc67ab7d-81e6-4321-a398-c5a74ea773fd_0.png"], "question": "What is the main cause of degradation in this image?\nA.missing tiles\nB.color distortion\nC.noise\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "fbe1628c-9066-4402-acb6-45e725cada7c", "images": ["Perception/single/fbe1628c-9066-4402-acb6-45e725cada7c_0.png"], "question": "What category of distortion does this image belong to?\nA.blur\nB.No distortion\nC.cloud\nD.noise", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "e5996296-c61e-4379-a6d2-a4b85695748e", "images": ["Perception/single/e5996296-c61e-4379-a6d2-a4b85695748e_0.png"], "question": "Is image stretching responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "316281bf-f0fd-4a2f-a63d-0df53f98744e", "images": ["Perception/paired/316281bf-f0fd-4a2f-a63d-0df53f98744e_0.png", "Perception/paired/316281bf-f0fd-4a2f-a63d-0df53f98744e_1.png"], "question": "Is spatially correlated noise the primary source of degradation in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "e4b27baf-61b4-4939-9d9f-04cbf45af1fa", "images": ["Description/single/e4b27baf-61b4-4939-9d9f-04cbf45af1fa_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe deadline noise introduces horizontal streaks across the image, disrupting the visual continuity and making features like water bodies and urban layouts difficult to discern. The distortion obscures fine details, such as road networks and building structures, significantly reducing the interpretability of the image for spatial analysis. The image quality is poor, with critical information heavily degraded by the noise.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "baf1228d-0884-4456-a802-0f3a714391b8", "images": ["Perception/paired/baf1228d-0884-4456-a802-0f3a714391b8_0.png", "Perception/paired/baf1228d-0884-4456-a802-0f3a714391b8_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of gaussian noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cee43947-c0da-4f54-95e5-bab2fe5a8b21", "images": ["Perception/paired/cee43947-c0da-4f54-95e5-bab2fe5a8b21_0.png", "Perception/paired/cee43947-c0da-4f54-95e5-bab2fe5a8b21_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.dead pixel\nB.No distortion\nC.missing tiles\nD.haze", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "11edd906-4e93-41e3-bb64-f73100333016", "images": ["Perception/paired/11edd906-4e93-41e3-bb64-f73100333016_0.png", "Perception/paired/11edd906-4e93-41e3-bb64-f73100333016_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.cloud\nB.No distortion\nC.color distortion\nD.blur", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3f739d1c-d501-4511-9574-cbf6959ea770", "images": ["Perception/single/3f739d1c-d501-4511-9574-cbf6959ea770_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "19f43dbf-1c25-41fe-86a1-84e2d0355a84", "images": ["Perception/paired/19f43dbf-1c25-41fe-86a1-84e2d0355a84_0.png", "Perception/paired/19f43dbf-1c25-41fe-86a1-84e2d0355a84_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "1efcc9c5-a198-4f6e-a123-c6c7db592dce", "images": ["Perception/single/1efcc9c5-a198-4f6e-a123-c6c7db592dce_0.png"], "question": "What category of distortion does this image belong to?\nA.missing tiles\nB.image compression\nC.noise\nD.No distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "1884641e-94d4-4a9a-9578-f2f37c519fda", "images": ["Description/single/1884641e-94d4-4a9a-9578-f2f37c519fda_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe haze significantly diminishes contrast and clarity, creating a washed-out appearance and obscuring fine details across the landscape. Key features such as roads and vegetation patterns are indistinct, making it challenging to discern spatial structures or land cover types. The image quality is poor, with limited usability for visual interpretation or analytical purposes.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "75f62bfa-c42a-42c5-9cb3-517a8dbd2ef3", "images": ["Description/single/75f62bfa-c42a-42c5-9cb3-517a8dbd2ef3_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The stripe noise introduces horizontal bands across the image, disrupting the uniform appearance of the forested area and creating visual distractions. The noise obscures fine details in the vegetation texture, making it difficult to discern subtle variations or patterns within the forest canopy. The image quality is moderately degraded, reducing its suitability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "6e09fea5-3ac1-434a-a4c2-2d003f561b03", "images": ["Perception/single/6e09fea5-3ac1-434a-a4c2-2d003f561b03_0.png"], "question": "Does gaussian noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "0254db38-6194-4077-b211-e9026ac911ec", "images": ["Perception/single/0254db38-6194-4077-b211-e9026ac911ec_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "50ce940e-f3d4-4a80-9084-4d3b9bdfdca2", "images": ["Perception/single/50ce940e-f3d4-4a80-9084-4d3b9bdfdca2_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "3435a62a-38f0-4766-af77-e46a418c9e48", "images": ["Perception/paired/3435a62a-38f0-4766-af77-e46a418c9e48_0.png", "Perception/paired/3435a62a-38f0-4766-af77-e46a418c9e48_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of dead pixel?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "c6349a1c-70b2-4462-816c-5b44ecdecabc", "images": ["Perception/paired/c6349a1c-70b2-4462-816c-5b44ecdecabc_0.png", "Perception/paired/c6349a1c-70b2-4462-816c-5b44ecdecabc_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.missing tiles\nB.dead pixel\nC.haze\nD.blur", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "63d1205c-9ba4-40b5-aef6-338dbf8a2748", "images": ["Description/single/63d1205c-9ba4-40b5-aef6-338dbf8a2748_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces noticeable blocky artifacts and blurring, causing building edges to appear less defined and vegetation to lose its natural texture. The distortion obscures fine details, making roads and smaller structures harder to distinguish and reducing the clarity of urban and natural features. The image quality is poor, significantly limiting its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "004ff6c6-b2b8-4187-b892-68de962914b4", "images": ["Perception/paired/004ff6c6-b2b8-4187-b892-68de962914b4_0.png", "Perception/paired/004ff6c6-b2b8-4187-b892-68de962914b4_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable cloud artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f658db4f-ce79-4544-a8e5-8c9f44a16e7b", "images": ["Perception/single/f658db4f-ce79-4544-a8e5-8c9f44a16e7b_0.png"], "question": "Does gaussian noise affect the image quality?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "15249af5-56f9-4654-871b-1c412107da10", "images": ["Perception/single/15249af5-56f9-4654-871b-1c412107da10_0.png"], "question": "Is dead pixel the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "92cd9ccd-eae0-489a-ac7d-b59a7580ca2c", "images": ["Description/single/92cd9ccd-eae0-489a-ac7d-b59a7580ca2c_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The impulse noise creates a speckled appearance across the image, disrupting the uniformity of surfaces and introducing distracting artifacts. Key features such as building outlines and road networks are obscured, making it difficult to discern structural details and spatial relationships. The image quality is poor, significantly hindering its usability for analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "f1f14773-d2da-4636-b834-2dfdb5535078", "images": ["Perception/single/f1f14773-d2da-4636-b834-2dfdb5535078_0.png"], "question": "Select all types of distortions affecting this image.\nA. dead pixel\nB. color distortion\nC. deadline noise\nD. image compression", "answer": "B,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "a9a0b7f1-ef3b-4dde-b277-a3ad8bd5ba08", "images": ["Perception/single/a9a0b7f1-ef3b-4dde-b277-a3ad8bd5ba08_0.png"], "question": "What is the main cause of degradation in this image?\nA.No distortion\nB.color distortion\nC.noise\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "64f77c54-0f1b-4606-ae3e-868cd325439c", "images": ["Perception/single/64f77c54-0f1b-4606-ae3e-868cd325439c_0.png"], "question": "Is motion blur responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "f1088a34-7321-4623-bfd5-650e00d3a69d", "images": ["Description/paired/f1088a34-7321-4623-bfd5-650e00d3a69d_0.png", "Description/paired/f1088a34-7321-4623-bfd5-650e00d3a69d_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 contains strong image compression artifacts, which manifest as blockiness and blurring, particularly noticeable in the darker regions. Therefore, Image 1 has higher overall quality due to the absence of any visible distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "df585853-4739-401e-ba70-5cc2e7d28930", "images": ["Perception/single/df585853-4739-401e-ba70-5cc2e7d28930_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "b02b51df-eafe-4b03-bb33-aa08637edf5a", "images": ["Perception/paired/b02b51df-eafe-4b03-bb33-aa08637edf5a_0.png", "Perception/paired/b02b51df-eafe-4b03-bb33-aa08637edf5a_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "063c3c91-2c04-4e41-8e26-f0917ba1fe8d", "images": ["Perception/paired/063c3c91-2c04-4e41-8e26-f0917ba1fe8d_0.png", "Perception/paired/063c3c91-2c04-4e41-8e26-f0917ba1fe8d_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.image stretching\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e2388669-1303-41a8-af21-6c120e7187e8", "images": ["Perception/single/e2388669-1303-41a8-af21-6c120e7187e8_0.png"], "question": "Does dead pixel affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "37d9a502-59ab-4c5d-9369-4fb3f63e366a", "images": ["Perception/paired/37d9a502-59ab-4c5d-9369-4fb3f63e366a_0.png", "Perception/paired/37d9a502-59ab-4c5d-9369-4fb3f63e366a_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.No distortion\nB.image stretching\nC.haze\nD.missing tiles", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "1f858a7d-6351-4391-9fe6-2d448995580b", "images": ["Perception/single/1f858a7d-6351-4391-9fe6-2d448995580b_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.blur\nB.image stretching\nC.cloud\nD.No distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "daec58a5-4f37-4657-97f4-9d6870714605", "images": ["Perception/paired/daec58a5-4f37-4657-97f4-9d6870714605_0.png", "Perception/paired/daec58a5-4f37-4657-97f4-9d6870714605_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of deadline noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "feec8ef1-a96e-443d-a3f9-a9f360361191", "images": ["Perception/single/feec8ef1-a96e-443d-a3f9-a9f360361191_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.striping\nB.speckle\nC.sidelobe\nD.ghosting", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "b0be1050-098e-41b6-aad5-50d9e1ebc2dc", "images": ["Perception/paired/b0be1050-098e-41b6-aad5-50d9e1ebc2dc_0.png", "Perception/paired/b0be1050-098e-41b6-aad5-50d9e1ebc2dc_1.png"], "question": "Identify the main distortion introduced between the two images.\nA.blur\nB.image compression\nC.image stretching\nD.noise", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6a2971ad-ca7f-4c10-a20c-6f647637fe38", "images": ["Perception/single/6a2971ad-ca7f-4c10-a20c-6f647637fe38_0.png"], "question": "Is image compression a dominant distortion in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "c6197ccf-f54b-483a-8e4b-87e069820509", "images": ["Perception/single/c6197ccf-f54b-483a-8e4b-87e069820509_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "3b9d4d4f-a9e4-4bda-88ee-245a6d4e3f86", "images": ["Perception/paired/3b9d4d4f-a9e4-4bda-88ee-245a6d4e3f86_0.png", "Perception/paired/3b9d4d4f-a9e4-4bda-88ee-245a6d4e3f86_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.No distortion\nB.blur\nC.noise\nD.cloud", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "662ff908-9b1f-45b4-b674-0dc218e6cb7b", "images": ["Description/paired/662ff908-9b1f-45b4-b674-0dc218e6cb7b_0.png", "Description/paired/662ff908-9b1f-45b4-b674-0dc218e6cb7b_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains moderate image compression artifacts, including blockiness and blurring, which reduce the clarity and detail of the image. Therefore, Image 1 has higher overall quality due to its lack of visible distortions and clearer visual presentation.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "9ec508d9-edc8-4e38-9523-c78891b19848", "images": ["Perception/single/9ec508d9-edc8-4e38-9523-c78891b19848_0.png"], "question": "Is the image impacted by color distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "d38e7ada-5f0d-4d46-8245-9c75d7b411f6", "images": ["Perception/paired/d38e7ada-5f0d-4d46-8245-9c75d7b411f6_0.png", "Perception/paired/d38e7ada-5f0d-4d46-8245-9c75d7b411f6_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.missing tiles\nB.No distortion\nC.noise\nD.image stretching", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9cf52a97-2cc2-4688-a323-b81f0a27089e", "images": ["Description/single/9cf52a97-2cc2-4688-a323-b81f0a27089e_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The image stretching causes noticeable distortion, elongating features such as roads and farmland boundaries, which disrupts their natural proportions. The stretched appearance reduces interpretability by making field shapes irregular and diminishing clarity in water body contours and urban layouts. The image quality is moderately degraded, affecting accurate visual analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "a0bf1635-c763-4513-bdd8-f2af7a76323a", "images": ["Perception/single/a0bf1635-c763-4513-bdd8-f2af7a76323a_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.striping\nB.sidelobe\nC.speckle\nD.ghosting", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "2c116058-c55a-429a-b07e-db639bafc155", "images": ["Description/paired/2c116058-c55a-429a-b07e-db639bafc155_0.png", "Description/paired/2c116058-c55a-429a-b07e-db639bafc155_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears clean and clear. Image 2 contains moderate cloud artifacts that obscure parts of the terrain, making it less visually clear. Therefore, Image 1 has higher overall quality due to the absence of any distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "82616f24-912d-4696-a14d-5c0f6c445a97", "images": ["Perception/single/82616f24-912d-4696-a14d-5c0f6c445a97_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.No distortion\nB.noise\nC.dead pixel\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "e9a0cb81-2df3-49e1-8bea-3fa06b8c52a5", "images": ["Perception/single/e9a0cb81-2df3-49e1-8bea-3fa06b8c52a5_0.png"], "question": "What visual defect does this image exhibit?\nA.image compression\nB.cloud\nC.noise\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "9d3bd989-c09b-43c2-b329-03132d03ac8c", "images": ["Perception/single/9d3bd989-c09b-43c2-b329-03132d03ac8c_0.png"], "question": "Does the image exhibit image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "d114f69b-9b4a-4528-a9e7-8ee97e3764c7", "images": ["Perception/paired/d114f69b-9b4a-4528-a9e7-8ee97e3764c7_0.png", "Perception/paired/d114f69b-9b4a-4528-a9e7-8ee97e3764c7_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5822934d-c731-400c-a571-f80d129cae53", "images": ["Perception/paired/5822934d-c731-400c-a571-f80d129cae53_0.png", "Perception/paired/5822934d-c731-400c-a571-f80d129cae53_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.No distortion\nB.haze\nC.image stretching\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "89a164b4-dd1d-4f1a-879b-98fca106a85f", "images": ["Perception/single/89a164b4-dd1d-4f1a-879b-98fca106a85f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "a1b25e52-95b6-4924-9d2d-afcb9c794fdd", "images": ["Perception/single/a1b25e52-95b6-4924-9d2d-afcb9c794fdd_0.png"], "question": "Does cloud lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "a226416d-d9fb-4fcf-87e0-6d0c0a8f0e2d", "images": ["Perception/single/a226416d-d9fb-4fcf-87e0-6d0c0a8f0e2d_0.png"], "question": "Is the image impacted by image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "bfc0e4c5-94df-4bf6-a917-eb1f8a7c0296", "images": ["Perception/paired/bfc0e4c5-94df-4bf6-a917-eb1f8a7c0296_0.png", "Perception/paired/bfc0e4c5-94df-4bf6-a917-eb1f8a7c0296_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of stripe noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0da32530-0961-4542-8ad7-2413d6aa4ab5", "images": ["Description/paired/0da32530-0961-4542-8ad7-2413d6aa4ab5_0.png", "Description/paired/0da32530-0961-4542-8ad7-2413d6aa4ab5_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears clean and high-quality with well-preserved details. Image 2 exhibits moderate compression artifacts, including blockiness and a loss of fine details, particularly noticeable in textured areas. Image 1 has higher overall quality because it is free of visible distortions, unlike Image 2, which suffers from compression-related degradation.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "6917e1d4-9a85-4d93-a3c3-7a62356c9f72", "images": ["Perception/paired/6917e1d4-9a85-4d93-a3c3-7a62356c9f72_0.png", "Perception/paired/6917e1d4-9a85-4d93-a3c3-7a62356c9f72_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable color distortion artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fa7f5594-a9db-4184-934b-278915394831", "images": ["Perception/single/fa7f5594-a9db-4184-934b-278915394831_0.png"], "question": "What type of distortion is visible here?\nA.image stretching\nB.dead pixel\nC.haze\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "56dc499b-e40b-423d-9522-10192fd5df0b", "images": ["Perception/single/56dc499b-e40b-423d-9522-10192fd5df0b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "ef05953c-eeea-41ed-9987-8ac2b8257616", "images": ["Perception/single/ef05953c-eeea-41ed-9987-8ac2b8257616_0.png"], "question": "What category of distortion does this image belong to?\nA.dead pixel\nB.No distortion\nC.image compression\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "4d2c4d20-ebbf-4d96-aad8-960e47d86811", "images": ["Perception/single/4d2c4d20-ebbf-4d96-aad8-960e47d86811_0.png"], "question": "What category of distortion does this image belong to?\nA.haze\nB.image compression\nC.noise\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f0e9523a-7f41-4a18-9dcd-46d31066b837", "images": ["Perception/paired/f0e9523a-7f41-4a18-9dcd-46d31066b837_0.png", "Perception/paired/f0e9523a-7f41-4a18-9dcd-46d31066b837_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.noise\nB.No distortion\nC.haze\nD.cloud", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "691c62fd-4c54-4743-8ad2-8dfdbd6a89b0", "images": ["Perception/single/691c62fd-4c54-4743-8ad2-8dfdbd6a89b0_0.png"], "question": "Does haze result in missing information?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "084d58b5-e370-4a62-bef7-56bc28dd44c5", "images": ["Perception/single/084d58b5-e370-4a62-bef7-56bc28dd44c5_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.striping\nC.sidelobe\nD.ghosting", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "11776070-85e5-4b46-a26e-a20b1c6bc7d3", "images": ["Perception/paired/11776070-85e5-4b46-a26e-a20b1c6bc7d3_0.png", "Perception/paired/11776070-85e5-4b46-a26e-a20b1c6bc7d3_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.noise\nB.image compression\nC.dead pixel\nD.missing tiles", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "f6358865-f260-4c8f-a4d9-2fb12e940a90", "images": ["Description/paired/f6358865-f260-4c8f-a4d9-2fb12e940a90_0.png", "Description/paired/f6358865-f260-4c8f-a4d9-2fb12e940a90_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears visually clean and sharp. Image 2 exhibits severe motion blur artifacts, making the image appear smeared and lacking in detail. Therefore, Image 1 has higher overall quality due to its clarity and absence of distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "ab90e6fe-7ab6-49cb-8f12-3562d730435d", "images": ["Description/single/ab90e6fe-7ab6-49cb-8f12-3562d730435d_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The stripe noise introduces vertical artifacts across the image, disrupting the natural continuity of features like roads and vegetation. These artifacts obscure fine details, making it difficult to discern smaller structures and diminishing the clarity of land cover patterns. The image quality is moderately degraded, impairing its usability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f99e2da4-2380-49fb-a561-2f0d2fb0d1d5", "images": ["Perception/single/f99e2da4-2380-49fb-a561-2f0d2fb0d1d5_0.png"], "question": "Does the image exhibit spatially correlated noise?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "29c10001-7868-4637-b00a-051c35bbba1c", "images": ["Perception/paired/29c10001-7868-4637-b00a-051c35bbba1c_0.png", "Perception/paired/29c10001-7868-4637-b00a-051c35bbba1c_1.png"], "question": "How much quality degradation do you observe in the distorted image versus the reference?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "67725c9b-0f49-428e-ae21-5a03ca518722", "images": ["Perception/single/67725c9b-0f49-428e-ae21-5a03ca518722_0.png"], "question": "What is the dominant distortion affecting this image?\nA.color distortion\nB.noise\nC.cloud\nD.missing tiles", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "f9cd48ef-bad7-4bdf-a9f0-47c81c90d64c", "images": ["Perception/paired/f9cd48ef-bad7-4bdf-a9f0-47c81c90d64c_0.png", "Perception/paired/f9cd48ef-bad7-4bdf-a9f0-47c81c90d64c_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.image compression\nB.image stretching\nC.haze\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "399f6ec7-8ed8-4bf7-ac83-82a6ccf4636a", "images": ["Description/single/399f6ec7-8ed8-4bf7-ac83-82a6ccf4636a_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Vertical black lines caused by severe dead pixels disrupt the natural texture of the landscape, creating artificial divisions that detract from visual coherence. These distortions obscure fine details in vegetation patterns and terrain features, reducing the image's utility for accurate analysis. The image quality is poor due to the prominent and pervasive artifacts.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "5076e979-b7bb-41e5-975d-e23734807b51", "images": ["Perception/single/5076e979-b7bb-41e5-975d-e23734807b51_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.striping\nB.ghosting\nC.speckle\nD.sidelobe", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "6c2ebdac-6f63-4111-96c6-afede4a1968b", "images": ["Perception/single/6c2ebdac-6f63-4111-96c6-afede4a1968b_0.png"], "question": "What is the dominant distortion affecting this image?\nA.color distortion\nB.cloud\nC.No distortion\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "d52163be-58eb-464e-9660-a16940f3175f", "images": ["Description/paired/d52163be-58eb-464e-9660-a16940f3175f_0.png", "Description/paired/d52163be-58eb-464e-9660-a16940f3175f_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains strong dead pixel artifacts, which manifest as numerous white specks scattered across the image, significantly degrading its visual quality. Therefore, Image 1 has higher overall quality due to the absence of distortions compared to the heavily artifact-laden Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "4f5e0c54-acec-4a3f-bad0-b1fb150b7c28", "images": ["Perception/paired/4f5e0c54-acec-4a3f-bad0-b1fb150b7c28_0.png", "Perception/paired/4f5e0c54-acec-4a3f-bad0-b1fb150b7c28_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b739394f-d378-4889-98ee-753658c60e5b", "images": ["Description/single/b739394f-d378-4889-98ee-753658c60e5b_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces blocky artifacts and color inconsistencies, disrupting the natural transitions between vegetation and bare land. The texture of the forested areas is heavily degraded, and the clarity of the winding road is compromised, making it difficult to discern fine details. The image quality is poor, significantly limiting its usability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "e2f2952c-78cb-4426-b0e9-8f9c18f60fc9", "images": ["Perception/single/e2f2952c-78cb-4426-b0e9-8f9c18f60fc9_0.png"], "question": "Is the image impacted by the combination of image stretching and missing tiles?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "a1a8e254-0e7f-4a55-8bb0-43be043da942", "images": ["Perception/single/a1a8e254-0e7f-4a55-8bb0-43be043da942_0.png"], "question": "Is haze responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "f15caf84-651b-4254-a736-5ae5836e7525", "images": ["Perception/single/f15caf84-651b-4254-a736-5ae5836e7525_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "36ffd73c-f594-4d22-a7a5-037dfca937e5", "images": ["Perception/single/36ffd73c-f594-4d22-a7a5-037dfca937e5_0.png"], "question": "Does deadline noise compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "931e18e1-a1e8-44cf-a22b-901c261fd268", "images": ["Perception/paired/931e18e1-a1e8-44cf-a22b-901c261fd268_0.png", "Perception/paired/931e18e1-a1e8-44cf-a22b-901c261fd268_1.png"], "question": "Which distortion most clearly appears in the degraded image?\nA.cloud\nB.image stretching\nC.image compression\nD.haze", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fb93a995-624a-4115-8f97-3de426c63687", "images": ["Perception/single/fb93a995-624a-4115-8f97-3de426c63687_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.haze\nC.missing tiles\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "0e3cf6e9-760b-4b97-bf91-1276f83474d0", "images": ["Perception/single/0e3cf6e9-760b-4b97-bf91-1276f83474d0_0.png"], "question": "What is the dominant distortion affecting this image?\nA.color distortion\nB.noise\nC.cloud\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "4d206a68-49e3-40af-a07d-22542d415af4", "images": ["Description/paired/4d206a68-49e3-40af-a07d-22542d415af4_0.png", "Description/paired/4d206a68-49e3-40af-a07d-22542d415af4_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and sharp. Image 2 exhibits moderate image compression artifacts, including blockiness and blurring, which degrade the overall clarity and detail. Therefore, Image 1 has higher overall quality due to its lack of distortions and superior visual clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "93edf44d-0e57-429b-890e-bceee0b7f4d3", "images": ["Perception/single/93edf44d-0e57-429b-890e-bceee0b7f4d3_0.png"], "question": "Is image compression responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "2936d67f-08eb-46d1-9d9b-d62c81231f6b", "images": ["Perception/single/2936d67f-08eb-46d1-9d9b-d62c81231f6b_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.missing tiles\nB.color distortion\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "889383b2-cd93-4083-8db5-d8afe1534aff", "images": ["Perception/single/889383b2-cd93-4083-8db5-d8afe1534aff_0.png"], "question": "Is image compression visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "dcbd027d-be9e-4ced-a072-871c5d2319b3", "images": ["Perception/single/dcbd027d-be9e-4ced-a072-871c5d2319b3_0.png"], "question": "Does motion blur reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "ad48f73e-4490-4430-8a46-d0495eb6d630", "images": ["Perception/paired/ad48f73e-4490-4430-8a46-d0495eb6d630_0.png", "Perception/paired/ad48f73e-4490-4430-8a46-d0495eb6d630_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "d3ec2eea-8891-439c-857a-d33883a9dd4f", "images": ["Perception/single/d3ec2eea-8891-439c-857a-d33883a9dd4f_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.image stretching\nB.dead pixel\nC.haze\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "f9628003-d41a-4239-b9a5-7f5e59838454", "images": ["Description/paired/f9628003-d41a-4239-b9a5-7f5e59838454_0.png", "Description/paired/f9628003-d41a-4239-b9a5-7f5e59838454_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears clean and high-quality with well-preserved details. Image 2 exhibits moderate compression artifacts, including blockiness and a loss of fine details, resulting in a visibly degraded appearance. Image 1 has higher overall quality because it retains more detail and lacks the compression artifacts present in Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "d3778ed1-e786-40f7-9c4b-67a7a1b2cd59", "images": ["Description/single/d3778ed1-e786-40f7-9c4b-67a7a1b2cd59_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces blocky artifacts and significant blurring, causing the building edges and vegetation patterns to appear irregular and fragmented. The distortion obscures fine details, such as the texture of vegetation and the clarity of road markings, reducing the image's interpretability for analysis. The image quality is poor, with substantial loss of visual fidelity and spatial information.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "6199c5f2-198b-4154-969a-6ac6cb92f653", "images": ["Perception/single/6199c5f2-198b-4154-969a-6ac6cb92f653_0.png"], "question": "Is cloud the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "e18b6439-c137-40fd-8929-edb6284e4f9d", "images": ["Description/single/e18b6439-c137-40fd-8929-edb6284e4f9d_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe color distortion causes unnatural purple and pink hues, significantly altering the visual appearance of vegetation and farmland. This distortion obscures fine details, making it difficult to distinguish between land cover types and reducing the clarity of structural features like roads and buildings. The image quality is poor, with compromised interpretability for analytical purposes.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "48a340b8-1d19-4455-ba6b-88209fdae012", "images": ["Perception/single/48a340b8-1d19-4455-ba6b-88209fdae012_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.dead pixel\nB.missing tiles\nC.image compression\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "ec5db546-4c3f-47af-af8e-582eafcc8e5c", "images": ["Perception/single/ec5db546-4c3f-47af-af8e-582eafcc8e5c_0.png"], "question": "Does stripe noise lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "b7384157-e6c8-472e-b804-35eebfcb5fdc", "images": ["Perception/single/b7384157-e6c8-472e-b804-35eebfcb5fdc_0.png"], "question": "Does gaussian noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "c90f1e3c-8ab3-4efe-93a6-561cbcdd45b9", "images": ["Perception/single/c90f1e3c-8ab3-4efe-93a6-561cbcdd45b9_0.png"], "question": "Does impulse noise compromise the data integrity?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "348c1f35-8b6d-466d-a36d-6921a0793473", "images": ["Perception/paired/348c1f35-8b6d-466d-a36d-6921a0793473_0.png", "Perception/paired/348c1f35-8b6d-466d-a36d-6921a0793473_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.image compression\nB.dead pixel\nC.No distortion\nD.image stretching", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ba197225-a0ef-4adf-bf65-23e4f865b3d4", "images": ["Perception/single/ba197225-a0ef-4adf-bf65-23e4f865b3d4_0.png"], "question": "Do visual cues of image stretching and image compression appear in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "3855a1d2-dfcb-445c-bfb0-052bc033287a", "images": ["Perception/single/3855a1d2-dfcb-445c-bfb0-052bc033287a_0.png"], "question": "Identify all distortions that degrade this remote sensing image from the options below.\nA. haze\nB. color distortion\nC. image stretching\nD. impulse noise", "answer": "C,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "ada75b8a-d8ff-41ac-b66d-b3b18f22cc5b", "images": ["Perception/single/ada75b8a-d8ff-41ac-b66d-b3b18f22cc5b_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.No distortion\nB.haze\nC.blur\nD.dead pixel", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "16e11e6d-4847-415b-bcd8-391f5e1c7c3a", "images": ["Perception/paired/16e11e6d-4847-415b-bcd8-391f5e1c7c3a_0.png", "Perception/paired/16e11e6d-4847-415b-bcd8-391f5e1c7c3a_1.png"], "question": "How would you grade the distortion intensity affecting Image 2 relative to its reference counterpart?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "c5af12f7-6236-47f1-a706-1ff7f4b9e0c6", "images": ["Perception/single/c5af12f7-6236-47f1-a706-1ff7f4b9e0c6_0.png"], "question": "Is dead pixel responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "74940158-275b-485b-bb21-3d0cf3e93bda", "images": ["Perception/single/74940158-275b-485b-bb21-3d0cf3e93bda_0.png"], "question": "What distortion is present in the image?\nA.image compression\nB.haze\nC.color distortion\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "659ba41a-0826-409c-9574-2dd9b44c8eab", "images": ["Perception/single/659ba41a-0826-409c-9574-2dd9b44c8eab_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "2c547af9-63aa-46b9-ab5f-1cd253caec5f", "images": ["Perception/single/2c547af9-63aa-46b9-ab5f-1cd253caec5f_0.png"], "question": "Is there image compression present in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "1207901a-740c-4275-ac0f-79f7d70fb977", "images": ["Description/single/1207901a-740c-4275-ac0f-79f7d70fb977_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces blocky artifacts and significant blurring, causing building edges to appear indistinct and vegetation to lose its natural texture. The compression obscures fine details, making features like road boundaries and small structures difficult to discern and reducing the image's analytical utility. The image quality is poor, with substantial degradation affecting visual clarity and interpretability.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "29e04f85-92e9-44fd-a5bf-ec15d0641c4e", "images": ["Perception/paired/29e04f85-92e9-44fd-a5bf-ec15d0641c4e_0.png", "Perception/paired/29e04f85-92e9-44fd-a5bf-ec15d0641c4e_1.png"], "question": "What degradation type transforms Image 1 into Image 2?\nA.missing tiles\nB.cloud\nC.image stretching\nD.image compression", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "4ead0300-15b1-4c3c-b521-8b3ea17d6a0d", "images": ["Perception/single/4ead0300-15b1-4c3c-b521-8b3ea17d6a0d_0.png"], "question": "Does image stretching affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "0bb79695-1024-44f5-8784-2905198039ac", "images": ["Perception/single/0bb79695-1024-44f5-8784-2905198039ac_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "ef8d2103-a28b-44c8-8090-2faf67b038ce", "images": ["Perception/single/ef8d2103-a28b-44c8-8090-2faf67b038ce_0.png"], "question": "Does image compression reduce the usability of the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "c19284ea-9e8e-4ba3-b804-d5812b1c0a72", "images": ["Perception/paired/c19284ea-9e8e-4ba3-b804-d5812b1c0a72_0.png", "Perception/paired/c19284ea-9e8e-4ba3-b804-d5812b1c0a72_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.noise\nB.image compression\nC.haze\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "01f85389-42d1-4cae-83de-fd0f80703327", "images": ["Perception/single/01f85389-42d1-4cae-83de-fd0f80703327_0.png"], "question": "What visual defect does this image exhibit?\nA.No distortion\nB.noise\nC.image compression\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "a474c196-7ce7-4f9b-98c5-3a840271b46e", "images": ["Perception/single/a474c196-7ce7-4f9b-98c5-3a840271b46e_0.png"], "question": "Is the image impacted by color distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "c6e1ebb1-5e4c-48da-b479-76124c828e95", "images": ["Perception/paired/c6e1ebb1-5e4c-48da-b479-76124c828e95_0.png", "Perception/paired/c6e1ebb1-5e4c-48da-b479-76124c828e95_1.png"], "question": "Compare Image 2 to Image 1 and choose the severity of distortion.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "da457508-656a-4c8d-a7af-c29531d337a1", "images": ["Perception/single/da457508-656a-4c8d-a7af-c29531d337a1_0.png"], "question": "From the list, which artifacts can be observed in this scene?\nA. motion blur\nB. cloud\nC. haze\nD. image stretching", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e41b642a-f3d6-4a22-8cc2-7975c082f4d4", "images": ["Perception/single/e41b642a-f3d6-4a22-8cc2-7975c082f4d4_0.png"], "question": "Does stripe noise reduce the usability of the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "2822e07c-4756-4c9e-a2d0-16cd926d346e", "images": ["Perception/paired/2822e07c-4756-4c9e-a2d0-16cd926d346e_0.png", "Perception/paired/2822e07c-4756-4c9e-a2d0-16cd926d346e_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.blur\nB.color distortion\nC.No distortion\nD.dead pixel", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "35271a59-4588-439a-aacd-0e47556be16b", "images": ["Perception/paired/35271a59-4588-439a-aacd-0e47556be16b_0.png", "Perception/paired/35271a59-4588-439a-aacd-0e47556be16b_1.png"], "question": "Does Image 2 exhibit image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "f279b573-e8fb-43e6-80dd-d6821ab83683", "images": ["Perception/single/f279b573-e8fb-43e6-80dd-d6821ab83683_0.png"], "question": "Does spatially correlated noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "ee51dc1e-4c17-424b-a51c-e1d6092434e9", "images": ["Perception/single/ee51dc1e-4c17-424b-a51c-e1d6092434e9_0.png"], "question": "Which of the following distortions are present in this image? (Select all that apply)\nA. spatially correlated noise\nB. dead pixel\nC. deadline noise\nD. motion blur", "answer": "A,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e2a7179b-2362-4153-9234-fb5bb03ddf04", "images": ["Perception/paired/e2a7179b-2362-4153-9234-fb5bb03ddf04_0.png", "Perception/paired/e2a7179b-2362-4153-9234-fb5bb03ddf04_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6b09c6e5-b9f6-4cfb-b361-77e96028d6b4", "images": ["Perception/single/6b09c6e5-b9f6-4cfb-b361-77e96028d6b4_0.png"], "question": "Does this image contain dead pixel?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "f3d62050-3d17-4ca6-aad6-d36fc796ba3c", "images": ["Perception/paired/f3d62050-3d17-4ca6-aad6-d36fc796ba3c_0.png", "Perception/paired/f3d62050-3d17-4ca6-aad6-d36fc796ba3c_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable color distortion artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9edc65c2-e5ab-4ce9-9d32-bd0eb9ac0976", "images": ["Perception/single/9edc65c2-e5ab-4ce9-9d32-bd0eb9ac0976_0.png"], "question": "Identify the main type of corruption in this image.\nA.dead pixel\nB.blur\nC.image stretching\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "9cf72e51-6c22-4438-9687-77e6737cf354", "images": ["Perception/paired/9cf72e51-6c22-4438-9687-77e6737cf354_0.png", "Perception/paired/9cf72e51-6c22-4438-9687-77e6737cf354_1.png"], "question": "Given that Image 1 is the reference and Image 2 is distorted, how severe is the degradation in Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "603b26e1-a5d0-428d-bf28-0d399c9798d1", "images": ["Perception/single/603b26e1-a5d0-428d-bf28-0d399c9798d1_0.png"], "question": "Identify the main type of corruption in this image.\nA.No distortion\nB.dead pixel\nC.image compression\nD.haze", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "af63e5e1-6cb3-4557-b9a0-82b5e528d31b", "images": ["Perception/single/af63e5e1-6cb3-4557-b9a0-82b5e528d31b_0.png"], "question": "Does image stretching obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "95eae6fc-23f6-4c63-8031-c9257533d7a9", "images": ["Description/single/95eae6fc-23f6-4c63-8031-c9257533d7a9_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe gaussian noise introduces a grainy texture across the image, obscuring fine details and creating a chaotic visual appearance. Key features such as roads, buildings, and vegetation patterns are difficult to discern, reducing the image's interpretability for analysis. The image quality is poor due to the overwhelming distortion.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "72ee82b2-4de5-440a-a1c2-9887d7ce70ea", "images": ["Perception/paired/72ee82b2-4de5-440a-a1c2-9887d7ce70ea_0.png", "Perception/paired/72ee82b2-4de5-440a-a1c2-9887d7ce70ea_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3b09cb14-c1c0-438f-99ea-001aca9f6ca3", "images": ["Perception/single/3b09cb14-c1c0-438f-99ea-001aca9f6ca3_0.png"], "question": "Does image compression result in missing information?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "66224fd1-596b-456b-8a28-ab7420fdfc89", "images": ["Perception/paired/66224fd1-596b-456b-8a28-ab7420fdfc89_0.png", "Perception/paired/66224fd1-596b-456b-8a28-ab7420fdfc89_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.haze\nB.No distortion\nC.image compression\nD.cloud", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "1ff8a4c4-882f-40cd-b7cb-d70799fdc0b5", "images": ["Perception/paired/1ff8a4c4-882f-40cd-b7cb-d70799fdc0b5_0.png", "Perception/paired/1ff8a4c4-882f-40cd-b7cb-d70799fdc0b5_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.haze\nB.missing tiles\nC.image compression\nD.image stretching", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a5ecf580-d255-4d86-bdf5-a3a2a52094ec", "images": ["Perception/single/a5ecf580-d255-4d86-bdf5-a3a2a52094ec_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.speckle\nC.ghosting\nD.striping", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "815f5045-05a8-49ee-995e-c2f2bbaa0be1", "images": ["Perception/paired/815f5045-05a8-49ee-995e-c2f2bbaa0be1_0.png", "Perception/paired/815f5045-05a8-49ee-995e-c2f2bbaa0be1_1.png"], "question": "Which distortion category describes the changes from Image 1 to Image 2?\nA.noise\nB.missing tiles\nC.image compression\nD.cloud", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "bf337083-face-4b12-bcd6-a5e466f7bb10", "images": ["Perception/paired/bf337083-face-4b12-bcd6-a5e466f7bb10_0.png", "Perception/paired/bf337083-face-4b12-bcd6-a5e466f7bb10_1.png"], "question": "Assess the distortion level in Image 2 relative to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "3498a2a4-f5a4-4b5c-b744-cb3ab2e184fd", "images": ["Description/single/3498a2a4-f5a4-4b5c-b744-cb3ab2e184fd_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Vertical black lines caused by dead pixels disrupt the natural texture of the vegetation, creating a striped appearance that distracts the viewer. These severe distortions obscure fine details, making it difficult to analyze the spatial distribution and density of vegetation. The image quality is poor due to the prominent and pervasive artifacts.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "af4d7fd9-a598-486d-8250-4e77a9fe51b8", "images": ["Perception/paired/af4d7fd9-a598-486d-8250-4e77a9fe51b8_0.png", "Perception/paired/af4d7fd9-a598-486d-8250-4e77a9fe51b8_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d6c32ca3-45f2-4cea-8642-969ac4db7c61", "images": ["Perception/single/d6c32ca3-45f2-4cea-8642-969ac4db7c61_0.png"], "question": "Does motion blur reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "a8935324-bacc-4301-8fcd-7a27535c4863", "images": ["Perception/single/a8935324-bacc-4301-8fcd-7a27535c4863_0.png"], "question": "Is the image impacted by image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "4fb14a8d-ed7c-4eda-af79-e5d80e1cfb44", "images": ["Perception/paired/4fb14a8d-ed7c-4eda-af79-e5d80e1cfb44_0.png", "Perception/paired/4fb14a8d-ed7c-4eda-af79-e5d80e1cfb44_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.dead pixel\nB.blur\nC.noise\nD.image compression", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6f7cf43d-8cb6-42fb-96ea-ff24b2e869af", "images": ["Perception/paired/6f7cf43d-8cb6-42fb-96ea-ff24b2e869af_0.png", "Perception/paired/6f7cf43d-8cb6-42fb-96ea-ff24b2e869af_1.png"], "question": "Which distortion type most likely affects Image 2 relative to Image 1?\nA.cloud\nB.dead pixel\nC.haze\nD.image stretching", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9e1653ed-49c6-4d6e-bdb0-70dd57894a10", "images": ["Description/paired/9e1653ed-49c6-4d6e-bdb0-70dd57894a10_0.png", "Description/paired/9e1653ed-49c6-4d6e-bdb0-70dd57894a10_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong image compression artifacts, including blockiness and a significant loss of detail, making the image appear pixelated and unclear. Image 2 shows no observable distortions and maintains a high level of detail and clarity. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior visual fidelity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "438fbaeb-b873-41a6-922b-3b65e8c238cb", "images": ["Perception/single/438fbaeb-b873-41a6-922b-3b65e8c238cb_0.png"], "question": "Does this image contain color distortion and impulse noise simultaneously?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "1a251c80-1e69-429a-9b5a-b4a326938bac", "images": ["Perception/single/1a251c80-1e69-429a-9b5a-b4a326938bac_0.png"], "question": "Is stripe noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "85fb13e9-cf45-41ee-8e8a-808b2232ae58", "images": ["Perception/paired/85fb13e9-cf45-41ee-8e8a-808b2232ae58_0.png", "Perception/paired/85fb13e9-cf45-41ee-8e8a-808b2232ae58_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.image compression\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "1dfd555b-e9cd-4de3-b516-3bfd27ef1598", "images": ["Perception/single/1dfd555b-e9cd-4de3-b516-3bfd27ef1598_0.png"], "question": "What category of distortion does this image belong to?\nA.cloud\nB.noise\nC.missing tiles\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "43f4644b-3e94-4662-9cdf-4a6fab6dd0f4", "images": ["Perception/single/43f4644b-3e94-4662-9cdf-4a6fab6dd0f4_0.png"], "question": "Does motion blur reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "abf61950-a8e0-437b-b797-8d1d392db916", "images": ["Perception/single/abf61950-a8e0-437b-b797-8d1d392db916_0.png"], "question": "Which distortion most significantly affects this image?\nA.missing tiles\nB.No distortion\nC.dead pixel\nD.image stretching", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "cd81133c-ceef-4f86-8080-b8cbc7bd14c8", "images": ["Perception/single/cd81133c-ceef-4f86-8080-b8cbc7bd14c8_0.png"], "question": "Does the image exhibit deadline noise?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "a9b0f83f-7336-4ed4-a356-72cf51aa8362", "images": ["Perception/single/a9b0f83f-7336-4ed4-a356-72cf51aa8362_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.ghosting\nB.speckle\nC.sidelobe\nD.striping", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "1c022f6d-223f-4e6a-b7cb-8519abddbe31", "images": ["Perception/single/1c022f6d-223f-4e6a-b7cb-8519abddbe31_0.png"], "question": "Is speckle noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "ecfd83e5-93bf-4921-b989-f06af57566dd", "images": ["Description/paired/ecfd83e5-93bf-4921-b989-f06af57566dd_0.png", "Description/paired/ecfd83e5-93bf-4921-b989-f06af57566dd_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears visually clean and high-quality. Image 2 contains severe stripe noise artifacts, which manifest as numerous horizontal lines and a grainy texture across the entire image. Image 1 has higher overall quality because it lacks the stripe noise and graininess present in Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "574a495e-e4ca-4b64-9bc1-e051de6864f1", "images": ["Perception/single/574a495e-e4ca-4b64-9bc1-e051de6864f1_0.png"], "question": "Is gaussian blur a critical issue in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "ca4965af-1108-4684-98ad-f0c2a79ee8af", "images": ["Perception/single/ca4965af-1108-4684-98ad-f0c2a79ee8af_0.png"], "question": "Does gaussian noise obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "f0eb74dc-a830-4690-bd7c-d5cbfd44d762", "images": ["Perception/single/f0eb74dc-a830-4690-bd7c-d5cbfd44d762_0.png"], "question": "Does this image contain gaussian blur and impulse noise simultaneously?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "56e5491d-4cd3-4129-8de7-36ed6ad3103b", "images": ["Perception/paired/56e5491d-4cd3-4129-8de7-36ed6ad3103b_0.png", "Perception/paired/56e5491d-4cd3-4129-8de7-36ed6ad3103b_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "83b471bf-647a-41a1-a361-c860c7e2cc0f", "images": ["Perception/single/83b471bf-647a-41a1-a361-c860c7e2cc0f_0.png"], "question": "Is image compression a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "72a71dcf-2f04-46ec-b285-f38fb76789b0", "images": ["Perception/paired/72a71dcf-2f04-46ec-b285-f38fb76789b0_0.png", "Perception/paired/72a71dcf-2f04-46ec-b285-f38fb76789b0_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b3d1642e-e4f6-4f75-a70d-bdc645f346aa", "images": ["Perception/paired/b3d1642e-e4f6-4f75-a70d-bdc645f346aa_0.png", "Perception/paired/b3d1642e-e4f6-4f75-a70d-bdc645f346aa_1.png"], "question": "Is haze visible in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "452b5f65-2141-490c-ad74-d96aab232a1a", "images": ["Perception/single/452b5f65-2141-490c-ad74-d96aab232a1a_0.png"], "question": "Is spatially correlated noise a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "b6ba5413-8c85-48a1-9c47-6cabdc73377f", "images": ["Perception/single/b6ba5413-8c85-48a1-9c47-6cabdc73377f_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.No distortion\nB.dead pixel\nC.image compression\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "54e87813-1f02-4f83-becb-8acbf631d321", "images": ["Perception/single/54e87813-1f02-4f83-becb-8acbf631d321_0.png"], "question": "From the list, which artifacts can be observed in this scene?\nA. spatially correlated noise\nB. gaussian blur\nC. missing tiles\nD. motion blur", "answer": "A,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "486db4b3-3111-4445-8001-d71400a4ad19", "images": ["Perception/single/486db4b3-3111-4445-8001-d71400a4ad19_0.png"], "question": "Does motion blur obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "84966afc-8031-42d3-8c27-fa9e973eff48", "images": ["Perception/paired/84966afc-8031-42d3-8c27-fa9e973eff48_0.png", "Perception/paired/84966afc-8031-42d3-8c27-fa9e973eff48_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a62f7534-1486-42de-8df5-fb344ed3f814", "images": ["Perception/single/a62f7534-1486-42de-8df5-fb344ed3f814_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.No distortion\nB.dead pixel\nC.haze\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "387646a6-a985-4400-b0d7-34215c2b179b", "images": ["Perception/single/387646a6-a985-4400-b0d7-34215c2b179b_0.png"], "question": "Which distortion most significantly affects this image?\nA.noise\nB.color distortion\nC.image stretching\nD.No distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "9ec8c248-17b5-4fe8-947b-1e7675054edb", "images": ["Perception/single/9ec8c248-17b5-4fe8-947b-1e7675054edb_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "bcb5d52b-f7d3-433e-8d0b-f2b7ca45c59a", "images": ["Perception/single/bcb5d52b-f7d3-433e-8d0b-f2b7ca45c59a_0.png"], "question": "Does image compression reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "eec83056-6fce-4f94-aa47-bdad67912b76", "images": ["Perception/single/eec83056-6fce-4f94-aa47-bdad67912b76_0.png"], "question": "Is image compression the main factor in this distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "65d3b770-61ac-4767-bd05-45ec52817486", "images": ["Perception/single/65d3b770-61ac-4767-bd05-45ec52817486_0.png"], "question": "Can color distortion and motion blur be observed at the same time in this image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "1ecdb23a-9676-4b89-bc64-e9f13175604e", "images": ["Perception/paired/1ecdb23a-9676-4b89-bc64-e9f13175604e_0.png", "Perception/paired/1ecdb23a-9676-4b89-bc64-e9f13175604e_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5090e950-7658-4881-b54d-f5583a97d613", "images": ["Perception/single/5090e950-7658-4881-b54d-f5583a97d613_0.png"], "question": "What distortion is present in the image?\nA.haze\nB.color distortion\nC.noise\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "327dfc61-49e7-4475-bbd3-33de97fbfab2", "images": ["Description/paired/327dfc61-49e7-4475-bbd3-33de97fbfab2_0.png", "Description/paired/327dfc61-49e7-4475-bbd3-33de97fbfab2_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains no observable distortions and appears clean and high-quality. Image 2 exhibits strong missing tiles artifacts, visible as a large white rectangular area obscuring significant portions of the image. Image 1 has higher overall quality because it is free of distortions, while Image 2 is heavily degraded by missing data.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "a91a2360-32c7-4b55-99fc-ed0c7158a7c9", "images": ["Perception/single/a91a2360-32c7-4b55-99fc-ed0c7158a7c9_0.png"], "question": "Does motion blur interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "8b4256a7-06ad-46be-96f8-2bce5df717a1", "images": ["Perception/single/8b4256a7-06ad-46be-96f8-2bce5df717a1_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "1440965b-42a0-4611-b521-2e66f7918bd7", "images": ["Perception/single/1440965b-42a0-4611-b521-2e66f7918bd7_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "478ab5e7-7363-459a-bc88-1dab81d3e258", "images": ["Perception/paired/478ab5e7-7363-459a-bc88-1dab81d3e258_0.png", "Perception/paired/478ab5e7-7363-459a-bc88-1dab81d3e258_1.png"], "question": "Which distortion category describes the changes from Image 1 to Image 2?\nA.image compression\nB.image stretching\nC.dead pixel\nD.noise", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "2aff0107-77dd-4114-a9da-46c569aff4ea", "images": ["Perception/single/2aff0107-77dd-4114-a9da-46c569aff4ea_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "505ca3d8-7b59-4adc-8eba-b1b9bc95ae12", "images": ["Perception/single/505ca3d8-7b59-4adc-8eba-b1b9bc95ae12_0.png"], "question": "What category of distortion does this image belong to?\nA.No distortion\nB.cloud\nC.missing tiles\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "3bbdec5f-019e-4842-a0df-3736e3ce7786", "images": ["Perception/single/3bbdec5f-019e-4842-a0df-3736e3ce7786_0.png"], "question": "Which distortion most significantly affects this image?\nA.No distortion\nB.color distortion\nC.image stretching\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "7aee99c5-b12f-4354-b942-9c075d82c010", "images": ["Perception/single/7aee99c5-b12f-4354-b942-9c075d82c010_0.png"], "question": "What category of distortion does this image belong to?\nA.noise\nB.blur\nC.color distortion\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "7d4bb3c4-c954-43fb-8526-0e2ea66890fd", "images": ["Perception/single/7d4bb3c4-c954-43fb-8526-0e2ea66890fd_0.png"], "question": "What is the dominant distortion affecting this image?\nA.color distortion\nB.missing tiles\nC.haze\nD.No distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "48c2f5c7-a9b8-44f3-b9fc-d0a3bdf4371b", "images": ["Perception/single/48c2f5c7-a9b8-44f3-b9fc-d0a3bdf4371b_0.png"], "question": "Is the image impacted by the combination of gaussian noise and image compression?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "2c8658eb-a52c-4970-9bf3-18f4bf4480ef", "images": ["Description/single/2c8658eb-a52c-4970-9bf3-18f4bf4480ef_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces significant blurring and blocky artifacts, causing building edges and urban structures to appear indistinct and fragmented. The loss of fine details and texture makes roads, intersections, and smaller features difficult to discern, reducing the image's interpretability for urban analysis. The overall image quality is poor, with substantial degradation in clarity and usability.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "c0f914e5-c9f7-4c93-bd70-55b6e24d492d", "images": ["Perception/single/c0f914e5-c9f7-4c93-bd70-55b6e24d492d_0.png"], "question": "Does this image contain spatially correlated noise?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "13a6b53b-1571-4748-ba11-281056f76e03", "images": ["Perception/single/13a6b53b-1571-4748-ba11-281056f76e03_0.png"], "question": "Does haze compromise the data integrity?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "5c90030c-0865-481c-a662-d479371e5a32", "images": ["Perception/paired/5c90030c-0865-481c-a662-d479371e5a32_0.png", "Perception/paired/5c90030c-0865-481c-a662-d479371e5a32_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable image compression artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5992e7fa-d925-4c3b-83ac-9e3435ba3276", "images": ["Perception/paired/5992e7fa-d925-4c3b-83ac-9e3435ba3276_0.png", "Perception/paired/5992e7fa-d925-4c3b-83ac-9e3435ba3276_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a8a36ac9-1c7c-4b89-b56b-f8efa483e892", "images": ["Perception/paired/a8a36ac9-1c7c-4b89-b56b-f8efa483e892_0.png", "Perception/paired/a8a36ac9-1c7c-4b89-b56b-f8efa483e892_1.png"], "question": "Is there image stretching present in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "e72e031f-83f5-43ad-a738-8710d656ae60", "images": ["Perception/single/e72e031f-83f5-43ad-a738-8710d656ae60_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "63ddbb11-d58b-4004-a8dd-f07b71e98c9d", "images": ["Perception/single/63ddbb11-d58b-4004-a8dd-f07b71e98c9d_0.png"], "question": "Does cloud reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "4074567a-d375-4bbb-b638-22f54a1b45cd", "images": ["Perception/paired/4074567a-d375-4bbb-b638-22f54a1b45cd_0.png", "Perception/paired/4074567a-d375-4bbb-b638-22f54a1b45cd_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "2c6ad5ef-eb59-45b4-a3a5-15f4d7a3b1f9", "images": ["Perception/single/2c6ad5ef-eb59-45b4-a3a5-15f4d7a3b1f9_0.png"], "question": "Is deadline noise visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "d67daa18-7f0f-4ee4-9661-e83eb3ff0951", "images": ["Perception/single/d67daa18-7f0f-4ee4-9661-e83eb3ff0951_0.png"], "question": "What is the dominant distortion in this image?\nA.haze\nB.No distortion\nC.image compression\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "f6d8c24a-521d-4437-bf1e-a7dfbe559a0a", "images": ["Perception/paired/f6d8c24a-521d-4437-bf1e-a7dfbe559a0a_0.png", "Perception/paired/f6d8c24a-521d-4437-bf1e-a7dfbe559a0a_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.blur\nB.No distortion\nC.image stretching\nD.dead pixel", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0b8df626-694e-4e72-b091-2d93352bdecd", "images": ["Perception/single/0b8df626-694e-4e72-b091-2d93352bdecd_0.png"], "question": "Does this image contain image stretching?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "e0a5c260-c188-419e-b1cc-1f29ebd07c1a", "images": ["Perception/single/e0a5c260-c188-419e-b1cc-1f29ebd07c1a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "55bcd9dd-72d5-4532-a234-2166849949e1", "images": ["Perception/single/55bcd9dd-72d5-4532-a234-2166849949e1_0.png"], "question": "Does image stretching lead to information loss?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "cdd075b2-3ed7-455c-85f0-89fae93b6623", "images": ["Perception/single/cdd075b2-3ed7-455c-85f0-89fae93b6623_0.png"], "question": "What type of distortion is visible here?\nA.image compression\nB.missing tiles\nC.color distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "a8a2ad95-9f76-4af1-af2c-c083afe4f05e", "images": ["Perception/single/a8a2ad95-9f76-4af1-af2c-c083afe4f05e_0.png"], "question": "What category of distortion does this image belong to?\nA.missing tiles\nB.cloud\nC.haze\nD.color distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "017675f3-d6fe-458f-a6ca-c8fa01664be9", "images": ["Description/single/017675f3-d6fe-458f-a6ca-c8fa01664be9_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces significant blurring and pixelation, causing building edges to appear indistinct and farmland to lose uniformity. The compression obscures fine details, making road networks and vegetation patterns difficult to interpret and reducing the analytical value of the image. The overall image quality is poor, with substantial degradation in clarity and detail.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "77a8a7f2-60d4-4229-b37a-293cc469b11c", "images": ["Perception/single/77a8a7f2-60d4-4229-b37a-293cc469b11c_0.png"], "question": "Is gaussian noise the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "716039be-06a0-42b6-a245-a08382440fb7", "images": ["Perception/single/716039be-06a0-42b6-a245-a08382440fb7_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "dbb9c5ad-7001-47ed-acb8-85d036b70583", "images": ["Perception/paired/dbb9c5ad-7001-47ed-acb8-85d036b70583_0.png", "Perception/paired/dbb9c5ad-7001-47ed-acb8-85d036b70583_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fbdcbbd6-98f4-4cb2-bdd2-456132c0182a", "images": ["Perception/single/fbdcbbd6-98f4-4cb2-bdd2-456132c0182a_0.png"], "question": "Identify all distortions that degrade this remote sensing image from the options below.\nA. missing tiles\nB. motion blur\nC. dead pixel\nD. haze", "answer": "B,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "10a6e233-75eb-4971-82b0-333efc303758", "images": ["Perception/paired/10a6e233-75eb-4971-82b0-333efc303758_0.png", "Perception/paired/10a6e233-75eb-4971-82b0-333efc303758_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable image compression artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f8442257-cf55-467e-9a31-4fa63d585957", "images": ["Perception/single/f8442257-cf55-467e-9a31-4fa63d585957_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "720baa18-7daf-439d-807c-3db97d948651", "images": ["Perception/single/720baa18-7daf-439d-807c-3db97d948651_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "ff28e613-3a03-47e5-a1a6-0124eb724b47", "images": ["Perception/paired/ff28e613-3a03-47e5-a1a6-0124eb724b47_0.png", "Perception/paired/ff28e613-3a03-47e5-a1a6-0124eb724b47_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable gaussian noise artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "10064ef4-c954-482a-834c-e81b408bcc67", "images": ["Perception/single/10064ef4-c954-482a-834c-e81b408bcc67_0.png"], "question": "What type of distortion is visible here?\nA.image compression\nB.No distortion\nC.image stretching\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "7d538de6-0502-4715-86dd-2b126d3ab124", "images": ["Description/paired/7d538de6-0502-4715-86dd-2b126d3ab124_0.png", "Description/paired/7d538de6-0502-4715-86dd-2b126d3ab124_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and sharp. Image 2 exhibits moderate image compression artifacts, including blockiness and a loss of fine detail, which make the image appear less clear. Therefore, Image 1 has higher overall quality due to its lack of distortions and superior visual clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "1a91ddbf-e80b-44e4-a1b8-498e5343ac31", "images": ["Perception/single/1a91ddbf-e80b-44e4-a1b8-498e5343ac31_0.png"], "question": "Which distortion most significantly affects this image?\nA.noise\nB.haze\nC.blur\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "895426da-d835-4484-b7b7-57b5d816b387", "images": ["Description/paired/895426da-d835-4484-b7b7-57b5d816b387_0.png", "Description/paired/895426da-d835-4484-b7b7-57b5d816b387_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong image compression artifacts, including noticeable blockiness and blurring, which significantly degrade the visual quality. Image 2 shows no observable distortions and maintains clear and detailed visual information. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "901473ba-721c-4784-b54b-d6af5969fa00", "images": ["Perception/single/901473ba-721c-4784-b54b-d6af5969fa00_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "4fe7eb76-be61-456c-bf29-46107dd6713f", "images": ["Perception/single/4fe7eb76-be61-456c-bf29-46107dd6713f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "11c61ea9-3675-41b2-9e36-3ee25d5f79b3", "images": ["Description/single/11c61ea9-3675-41b2-9e36-3ee25d5f79b3_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Moderate color distortion causes a dulling effect, reducing the vibrancy of vegetation and making the landscape appear less natural. This distortion diminishes the clarity of fine details, such as individual tree textures and subtle variations in ground cover, which are crucial for accurate interpretation. The overall image quality is moderately degraded, impacting its usability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "0887d474-155b-4e3f-b198-08dc0ed76149", "images": ["Perception/single/0887d474-155b-4e3f-b198-08dc0ed76149_0.png"], "question": "Identify the main type of corruption in this image.\nA.noise\nB.cloud\nC.missing tiles\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "729db63c-3c9f-4e80-92dd-d791d1a8289f", "images": ["Description/paired/729db63c-3c9f-4e80-92dd-d791d1a8289f_0.png", "Description/paired/729db63c-3c9f-4e80-92dd-d791d1a8289f_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits moderate motion blur, evident in the smearing of edges and reduced clarity of fine details, particularly in the vegetation and building structures. Image 2 shows no observable distortions, with sharp edges and well-defined details throughout the scene. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior clarity compared to the blurred Image 1.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "e8011ba8-d9d1-4086-9d8d-703444cf2def", "images": ["Perception/single/e8011ba8-d9d1-4086-9d8d-703444cf2def_0.png"], "question": "Identify the main type of corruption in this image.\nA.cloud\nB.color distortion\nC.image compression\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "a6f031dd-d6ba-4b2f-8e95-9f6987af767f", "images": ["Perception/paired/a6f031dd-d6ba-4b2f-8e95-9f6987af767f_0.png", "Perception/paired/a6f031dd-d6ba-4b2f-8e95-9f6987af767f_1.png"], "question": "Evaluate the visual quality gap between the reference and degraded images using the three severity levels.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "272c7047-4bc5-49d7-ac50-5fd59b1534fc", "images": ["Perception/paired/272c7047-4bc5-49d7-ac50-5fd59b1534fc_0.png", "Perception/paired/272c7047-4bc5-49d7-ac50-5fd59b1534fc_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "689dc716-f613-488f-a3f3-7436243e45f7", "images": ["Perception/paired/689dc716-f613-488f-a3f3-7436243e45f7_0.png", "Perception/paired/689dc716-f613-488f-a3f3-7436243e45f7_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.haze\nB.No distortion\nC.image compression\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "538221a1-4109-40a6-80f5-9069bf937992", "images": ["Perception/paired/538221a1-4109-40a6-80f5-9069bf937992_0.png", "Perception/paired/538221a1-4109-40a6-80f5-9069bf937992_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d8ef66a8-d2ee-4571-8fe9-ced87b8d5012", "images": ["Perception/single/d8ef66a8-d2ee-4571-8fe9-ced87b8d5012_0.png"], "question": "Does this image contain gaussian blur?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "b45767e6-9a7c-4533-8d87-c461b569f758", "images": ["Perception/single/b45767e6-9a7c-4533-8d87-c461b569f758_0.png"], "question": "Does haze result in missing information?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "97da2cd5-cb0e-43f0-9b2a-ccc5631c540e", "images": ["Description/paired/97da2cd5-cb0e-43f0-9b2a-ccc5631c540e_0.png", "Description/paired/97da2cd5-cb0e-43f0-9b2a-ccc5631c540e_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains moderate dead pixel artifacts, which appear as numerous small black dots scattered across the entire image. Image 2 has no observable distortions and appears clean and clear. Therefore, Image 2 has higher overall quality due to the absence of any visible artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "c4840fd7-49ba-472e-a55a-ec59b3ec7ab1", "images": ["Perception/single/c4840fd7-49ba-472e-a55a-ec59b3ec7ab1_0.png"], "question": "Is gaussian noise a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "28372425-94bf-4198-886e-e12f185391d8", "images": ["Perception/single/28372425-94bf-4198-886e-e12f185391d8_0.png"], "question": "Does dead pixel lead to information loss?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "196784f8-686b-4c72-bb28-0f75da2d4f27", "images": ["Perception/paired/196784f8-686b-4c72-bb28-0f75da2d4f27_0.png", "Perception/paired/196784f8-686b-4c72-bb28-0f75da2d4f27_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3c240387-08c5-4ada-9dfe-987a65bd2f03", "images": ["Perception/single/3c240387-08c5-4ada-9dfe-987a65bd2f03_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "eaa944da-b561-4ed7-8b9c-fda931e78573", "images": ["Perception/single/eaa944da-b561-4ed7-8b9c-fda931e78573_0.png"], "question": "What form of distortion is most apparent here?\nA.image stretching\nB.haze\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "8d4f9743-9bfd-452d-98e4-7cfdbeab3c0a", "images": ["Perception/single/8d4f9743-9bfd-452d-98e4-7cfdbeab3c0a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "b37898a8-396c-424e-a5d1-f984c6e01292", "images": ["Perception/single/b37898a8-396c-424e-a5d1-f984c6e01292_0.png"], "question": "What type of distortion is visible here?\nA.cloud\nB.image stretching\nC.blur\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "f4d85966-d4ca-4e15-a584-49b4eb611bd2", "images": ["Perception/single/f4d85966-d4ca-4e15-a584-49b4eb611bd2_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "20054048-86bb-4cb3-8dca-4adc49239715", "images": ["Perception/single/20054048-86bb-4cb3-8dca-4adc49239715_0.png"], "question": "Is dead pixel the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "cbf9e819-fa08-4c62-8875-3ab3937e49b1", "images": ["Perception/single/cbf9e819-fa08-4c62-8875-3ab3937e49b1_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "f8a63eb3-f0c3-4a13-8d58-cf28425c3f99", "images": ["Perception/single/f8a63eb3-f0c3-4a13-8d58-cf28425c3f99_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "fa2d9b19-ae85-474c-a108-d06430366eef", "images": ["Perception/single/fa2d9b19-ae85-474c-a108-d06430366eef_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.ghosting\nC.speckle\nD.striping", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "d6265df9-3350-4421-b944-f88bb91cfdae", "images": ["Perception/single/d6265df9-3350-4421-b944-f88bb91cfdae_0.png"], "question": "Identify the main type of corruption in this image.\nA.cloud\nB.noise\nC.blur\nD.image compression", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "434b4427-7f7f-4a97-88bc-edde65dc3fdc", "images": ["Description/single/434b4427-7f7f-4a97-88bc-edde65dc3fdc_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe spatially correlated noise creates a grainy texture that obscures fine details and introduces unnatural color variations across the image. Building edges and structural outlines are heavily blurred, making it difficult to distinguish individual features or assess spatial relationships. The image quality is poor, significantly limiting its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "2728f56d-6a0b-4da7-ad81-bea94df09989", "images": ["Perception/single/2728f56d-6a0b-4da7-ad81-bea94df09989_0.png"], "question": "What type of distortion is visible here?\nA.image stretching\nB.noise\nC.cloud\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "454d97b6-8bc1-4ee8-a2eb-540dfff5fd03", "images": ["Perception/paired/454d97b6-8bc1-4ee8-a2eb-540dfff5fd03_0.png", "Perception/paired/454d97b6-8bc1-4ee8-a2eb-540dfff5fd03_1.png"], "question": "Identify the main distortion introduced between the two images.\nA.image compression\nB.haze\nC.blur\nD.missing tiles", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "00b96af5-4a9b-40db-bdad-40816315354b", "images": ["Perception/single/00b96af5-4a9b-40db-bdad-40816315354b_0.png"], "question": "What type of distortion is visible here?\nA.cloud\nB.No distortion\nC.image stretching\nD.image compression", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "a165f7d2-1d16-490a-9818-042d7d403138", "images": ["Perception/single/a165f7d2-1d16-490a-9818-042d7d403138_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "fd97263e-496e-438d-b4e5-7b95686be708", "images": ["Perception/paired/fd97263e-496e-438d-b4e5-7b95686be708_0.png", "Perception/paired/fd97263e-496e-438d-b4e5-7b95686be708_1.png"], "question": "What artifact has been applied to Image 2 when compared to Image 1?\nA.blur\nB.color distortion\nC.noise\nD.haze", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "8c65a7fb-525b-4920-bc6a-5f5106c6397f", "images": ["Perception/single/8c65a7fb-525b-4920-bc6a-5f5106c6397f_0.png"], "question": "Is gaussian noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "a826487f-ac56-402f-b718-11081e3cb15d", "images": ["Perception/single/a826487f-ac56-402f-b718-11081e3cb15d_0.png"], "question": "Which distortion most significantly affects this image?\nA.dead pixel\nB.missing tiles\nC.No distortion\nD.image stretching", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "75338885-982c-41ec-ac1c-03e27de65d4f", "images": ["Perception/single/75338885-982c-41ec-ac1c-03e27de65d4f_0.png"], "question": "Is image stretching visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "422d4050-4ada-43a7-9107-63eb610b70f8", "images": ["Perception/single/422d4050-4ada-43a7-9107-63eb610b70f8_0.png"], "question": "Identify the main type of corruption in this image.\nA.cloud\nB.color distortion\nC.No distortion\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "0f8c1857-bc9d-4c98-bcc0-2add92993917", "images": ["Perception/single/0f8c1857-bc9d-4c98-bcc0-2add92993917_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "c7977dd5-b3b6-4bff-9eb1-1a0ff0728225", "images": ["Description/single/c7977dd5-b3b6-4bff-9eb1-1a0ff0728225_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The missing tiles create large blank areas that disrupt the continuity of the landscape, making it difficult to visually interpret the spatial relationships between features. Key details such as urban structures and road networks are fragmented, significantly reducing the ability to analyze land use and connectivity. The image quality is poor due to the severe loss of information and visual coherence.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "4dbd0e98-e3e3-4780-8af8-bf1d722f2508", "images": ["Perception/paired/4dbd0e98-e3e3-4780-8af8-bf1d722f2508_0.png", "Perception/paired/4dbd0e98-e3e3-4780-8af8-bf1d722f2508_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of missing tiles?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b0399cc6-47be-4988-a405-19bbad590f46", "images": ["Description/paired/b0399cc6-47be-4988-a405-19bbad590f46_0.png", "Description/paired/b0399cc6-47be-4988-a405-19bbad590f46_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears visually clean and high-quality. Image 2 contains strong image stretching artifacts, which manifest as elongated and distorted features that disrupt the natural appearance of the terrain. Therefore, Image 1 has higher overall quality due to the absence of distortions and artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "827147da-096b-4aeb-9bfd-29820bedadb1", "images": ["Perception/single/827147da-096b-4aeb-9bfd-29820bedadb1_0.png"], "question": "Is dead pixel responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "aacf3246-b938-4ab9-b97a-35d6ecdf3d4f", "images": ["Perception/single/aacf3246-b938-4ab9-b97a-35d6ecdf3d4f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "7d3ef303-12a1-45c1-9e95-e0b84cdc74dc", "images": ["Perception/single/7d3ef303-12a1-45c1-9e95-e0b84cdc74dc_0.png"], "question": "What is the dominant distortion in this image?\nA.No distortion\nB.noise\nC.haze\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "8706db9c-4a82-474b-8a5b-2deed6a3d904", "images": ["Description/paired/8706db9c-4a82-474b-8a5b-2deed6a3d904_0.png", "Description/paired/8706db9c-4a82-474b-8a5b-2deed6a3d904_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits moderate Gaussian blur artifacts, making the details appear soft and less defined. Image 2 shows no observable distortions and maintains clear and sharp details. Therefore, Image 2 has higher overall quality due to its lack of distortions and better-defined features.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "4f32fd10-4b66-4267-a7c2-ed5393c6410c", "images": ["Perception/single/4f32fd10-4b66-4267-a7c2-ed5393c6410c_0.png"], "question": "Is impulse noise a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "38688ab0-51b1-4aec-aa0a-1b99c1c5686a", "images": ["Perception/paired/38688ab0-51b1-4aec-aa0a-1b99c1c5686a_0.png", "Perception/paired/38688ab0-51b1-4aec-aa0a-1b99c1c5686a_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e7a79529-05fc-47ec-807b-a5e688734517", "images": ["Perception/single/e7a79529-05fc-47ec-807b-a5e688734517_0.png"], "question": "Are cloud and image stretching present together in the scene?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "d8cbbc9e-be1d-483e-a668-0368d635ba23", "images": ["Perception/paired/d8cbbc9e-be1d-483e-a668-0368d635ba23_0.png", "Perception/paired/d8cbbc9e-be1d-483e-a668-0368d635ba23_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.missing tiles\nB.image compression\nC.No distortion\nD.cloud", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "daf67cad-2b9c-47d6-b939-9d1922937ca1", "images": ["Perception/single/daf67cad-2b9c-47d6-b939-9d1922937ca1_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.striping\nB.speckle\nC.sidelobe\nD.ghosting", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "dbb50734-84af-4570-afa5-3fbddb8ec30b", "images": ["Description/single/dbb50734-84af-4570-afa5-3fbddb8ec30b_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe dead pixels create a dense speckled pattern that obscures the structural details of buildings and roads, making them difficult to discern.  \nThe distortion disrupts spatial continuity, rendering features like intersections and vegetation boundaries indistinguishable and reducing the image's analytical utility.  \nThe image quality is poor due to the overwhelming noise and loss of clarity.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "872b3d08-f826-4d68-9174-bd23184c4c42", "images": ["Perception/single/872b3d08-f826-4d68-9174-bd23184c4c42_0.png"], "question": "From the list, which artifacts can be observed in this scene?\nA. impulse noise\nB. image stretching\nC. haze\nD. dead pixel", "answer": "B,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "31abc33c-d7e8-4ef5-88df-725ab64cb8d4", "images": ["Perception/paired/31abc33c-d7e8-4ef5-88df-725ab64cb8d4_0.png", "Perception/paired/31abc33c-d7e8-4ef5-88df-725ab64cb8d4_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.haze\nB.noise\nC.image stretching\nD.missing tiles", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "b1f1faac-dc2c-4c8d-857d-27b4fc2d16c7", "images": ["Perception/single/b1f1faac-dc2c-4c8d-857d-27b4fc2d16c7_0.png"], "question": "What distortion is present in the image?\nA.No distortion\nB.haze\nC.color distortion\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "13f53386-9da4-44d1-9122-cdd014cbdafa", "images": ["Perception/paired/13f53386-9da4-44d1-9122-cdd014cbdafa_0.png", "Perception/paired/13f53386-9da4-44d1-9122-cdd014cbdafa_1.png"], "question": "Does gaussian blur affect the quality of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "150459d0-8218-4dfb-abbd-2181839d4ccc", "images": ["Perception/paired/150459d0-8218-4dfb-abbd-2181839d4ccc_0.png", "Perception/paired/150459d0-8218-4dfb-abbd-2181839d4ccc_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fee64a83-3231-4e26-8473-d2b46aca210c", "images": ["Perception/single/fee64a83-3231-4e26-8473-d2b46aca210c_0.png"], "question": "What type of distortion is visible here?\nA.missing tiles\nB.haze\nC.image compression\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "0a3bd194-55e6-4ae8-9c3f-780723614479", "images": ["Perception/single/0a3bd194-55e6-4ae8-9c3f-780723614479_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.No distortion\nB.dead pixel\nC.image stretching\nD.haze", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "7594e304-d7df-4dfb-b53d-ece818a084ce", "images": ["Perception/single/7594e304-d7df-4dfb-b53d-ece818a084ce_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "9f4d14a6-c24f-422b-a437-63348bd1182e", "images": ["Perception/paired/9f4d14a6-c24f-422b-a437-63348bd1182e_0.png", "Perception/paired/9f4d14a6-c24f-422b-a437-63348bd1182e_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.image compression\nB.image stretching\nC.haze\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "62f551ee-588b-477d-a01b-637b35d24797", "images": ["Perception/paired/62f551ee-588b-477d-a01b-637b35d24797_0.png", "Perception/paired/62f551ee-588b-477d-a01b-637b35d24797_1.png"], "question": "How would you rate the degradation severity in Image 2 compared to the reference Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "14a4d36c-b4a3-4c70-9545-516dc744e2be", "images": ["Perception/single/14a4d36c-b4a3-4c70-9545-516dc744e2be_0.png"], "question": "Does spatially correlated noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "21e8773a-d358-4246-8f87-b7e5f1d810cd", "images": ["Perception/single/21e8773a-d358-4246-8f87-b7e5f1d810cd_0.png"], "question": "Does image stretching lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "a6997cf6-d05c-4287-8466-15f5a6a8c2fb", "images": ["Perception/single/a6997cf6-d05c-4287-8466-15f5a6a8c2fb_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "980fd7c1-2a1c-410d-96b5-80264dc2c34a", "images": ["Perception/single/980fd7c1-2a1c-410d-96b5-80264dc2c34a_0.png"], "question": "Is dead pixel present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "f595f97e-5f26-4e7a-a14a-e1f4e3e62860", "images": ["Perception/single/f595f97e-5f26-4e7a-a14a-e1f4e3e62860_0.png"], "question": "Is gaussian noise the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "1ef70b78-2a80-462c-a9e3-814b90f0108c", "images": ["Perception/single/1ef70b78-2a80-462c-a9e3-814b90f0108c_0.png"], "question": "What is the primary distortion type in this image?\nA.cloud\nB.haze\nC.missing tiles\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "8607743e-079d-4a06-96a5-49ff3d688d04", "images": ["Perception/paired/8607743e-079d-4a06-96a5-49ff3d688d04_0.png", "Perception/paired/8607743e-079d-4a06-96a5-49ff3d688d04_1.png"], "question": "Can gaussian noise be observed in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "3f2e063e-4173-4896-b44b-5f3f8b0fa74b", "images": ["Perception/single/3f2e063e-4173-4896-b44b-5f3f8b0fa74b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "de59f6b4-77d8-43de-9034-951af4006fa5", "images": ["Perception/single/de59f6b4-77d8-43de-9034-951af4006fa5_0.png"], "question": "Does this image contain image stretching?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "9f295a48-0c46-4f2c-96f8-25256bd6895c", "images": ["Perception/single/9f295a48-0c46-4f2c-96f8-25256bd6895c_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.noise\nB.color distortion\nC.image stretching\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "a5804dee-9d31-4d24-a819-58dc9c22883f", "images": ["Perception/single/a5804dee-9d31-4d24-a819-58dc9c22883f_0.png"], "question": "Does deadline noise reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "82cded83-989a-4718-8702-5bb81e21960b", "images": ["Perception/paired/82cded83-989a-4718-8702-5bb81e21960b_0.png", "Perception/paired/82cded83-989a-4718-8702-5bb81e21960b_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable image stretching artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0658551b-9872-4bd0-a25f-cfb9f645a8f6", "images": ["Perception/single/0658551b-9872-4bd0-a25f-cfb9f645a8f6_0.png"], "question": "What type of distortion is visible here?\nA.No distortion\nB.blur\nC.color distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "88a546f9-e242-433b-a718-3829e5d334a7", "images": ["Perception/single/88a546f9-e242-433b-a718-3829e5d334a7_0.png"], "question": "What is the dominant distortion in this image?\nA.haze\nB.No distortion\nC.dead pixel\nD.blur", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "00ace6e2-050f-40d7-8563-8e4568b9e9ac", "images": ["Perception/paired/00ace6e2-050f-40d7-8563-8e4568b9e9ac_0.png", "Perception/paired/00ace6e2-050f-40d7-8563-8e4568b9e9ac_1.png"], "question": "Is image stretching present and significant in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "e0b1217e-5484-496d-97e8-0712a3411fca", "images": ["Perception/single/e0b1217e-5484-496d-97e8-0712a3411fca_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "081feb04-3874-4f2e-b2ca-1a39a1e9642b", "images": ["Perception/single/081feb04-3874-4f2e-b2ca-1a39a1e9642b_0.png"], "question": "Is image compression a dominant distortion in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "5e7e0e77-4e6c-47ec-851f-1ab068b602bc", "images": ["Perception/single/5e7e0e77-4e6c-47ec-851f-1ab068b602bc_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.color distortion\nB.dead pixel\nC.haze\nD.noise", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "0179505c-ec85-4573-a109-eedb6c2a17cc", "images": ["Perception/paired/0179505c-ec85-4573-a109-eedb6c2a17cc_0.png", "Perception/paired/0179505c-ec85-4573-a109-eedb6c2a17cc_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "54f4b973-892f-458f-bea6-23462cc5ffc5", "images": ["Perception/single/54f4b973-892f-458f-bea6-23462cc5ffc5_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.cloud\nB.color distortion\nC.image compression\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "bccece94-3f67-4920-ab49-50f14c7531fb", "images": ["Perception/single/bccece94-3f67-4920-ab49-50f14c7531fb_0.png"], "question": "What form of distortion is most apparent here?\nA.haze\nB.missing tiles\nC.dead pixel\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "8776cc73-f949-44eb-bf71-b2b376d5944f", "images": ["Perception/single/8776cc73-f949-44eb-bf71-b2b376d5944f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "cb635704-7231-42e8-a246-aaf2faadbff9", "images": ["Perception/single/cb635704-7231-42e8-a246-aaf2faadbff9_0.png"], "question": "Identify the main type of corruption in this image.\nA.dead pixel\nB.blur\nC.image stretching\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "28faec94-f23d-44c0-b0d7-8227fac31887", "images": ["Perception/single/28faec94-f23d-44c0-b0d7-8227fac31887_0.png"], "question": "What is the dominant distortion in this image?\nA.haze\nB.dead pixel\nC.No distortion\nD.blur", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "cacef5ba-7ede-4bc8-afe3-7062371a5e07", "images": ["Perception/single/cacef5ba-7ede-4bc8-afe3-7062371a5e07_0.png"], "question": "What is the primary distortion type in this image?\nA.image stretching\nB.noise\nC.No distortion\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "b168c372-0935-4ad6-a1fd-5f6ec07266d4", "images": ["Description/single/b168c372-0935-4ad6-a1fd-5f6ec07266d4_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Moderate motion blur causes a noticeable softening of edges, making individual features like trees and ground patterns appear less distinct. The blurring diminishes the ability to discern fine details, such as the precise shapes and boundaries of vegetation and terrain features. The image quality is moderately degraded, reducing its suitability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "50b6bbe3-0832-4db1-8c44-5f7a6bd59d15", "images": ["Description/paired/50b6bbe3-0832-4db1-8c44-5f7a6bd59d15_0.png", "Description/paired/50b6bbe3-0832-4db1-8c44-5f7a6bd59d15_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 shows no observable distortions and appears clean, sharp, and free of artifacts. Image 2 exhibits severe motion blur, causing significant loss of detail and smearing across the entire image. Image 1 has higher overall quality due to its clarity and lack of distortions compared to the heavily degraded Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "f6408f8f-f8d4-4f04-badf-8e75adca193d", "images": ["Perception/single/f6408f8f-f8d4-4f04-badf-8e75adca193d_0.png"], "question": "Does deadline noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "0f648491-5c76-4f95-9c0a-864c99f1b156", "images": ["Perception/single/0f648491-5c76-4f95-9c0a-864c99f1b156_0.png"], "question": "Which of the following distortions are present in this image? (Select all that apply)\nA. gaussian noise\nB. missing tiles\nC. motion blur\nD. gaussian blur", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e6b97baf-8115-4f01-a2a2-8bac3e64f252", "images": ["Perception/single/e6b97baf-8115-4f01-a2a2-8bac3e64f252_0.png"], "question": "Does sidelobe interference reduce the usability of the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "9f66e6af-9f7b-45da-ae70-321c86d15416", "images": ["Perception/single/9f66e6af-9f7b-45da-ae70-321c86d15416_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.haze\nB.dead pixel\nC.image stretching\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "584629e8-97a7-4027-a258-8b4893856fab", "images": ["Perception/single/584629e8-97a7-4027-a258-8b4893856fab_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "5c492d6d-1921-4ee9-a766-070d22f3538e", "images": ["Description/paired/5c492d6d-1921-4ee9-a766-070d22f3538e_0.png", "Description/paired/5c492d6d-1921-4ee9-a766-070d22f3538e_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits moderate color distortion, with an unnatural magenta hue dominating the scene and obscuring finer details. Image 2 shows no observable distortions, maintaining natural colors and better clarity. Therefore, Image 2 has higher overall quality due to its accurate color representation and lack of visible artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "a405a038-e8bb-485d-808d-83f1eca86d39", "images": ["Perception/single/a405a038-e8bb-485d-808d-83f1eca86d39_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.noise\nB.haze\nC.dead pixel\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "60045d8a-fb19-4b13-b1b8-7a5b189a8356", "images": ["Perception/single/60045d8a-fb19-4b13-b1b8-7a5b189a8356_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.dead pixel\nB.noise\nC.image compression\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "06a80fa0-25c2-4ba2-a2d1-fdbfdf64ae75", "images": ["Perception/single/06a80fa0-25c2-4ba2-a2d1-fdbfdf64ae75_0.png"], "question": "Is color distortion the main factor in this distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "410ee4bf-4ac3-40dc-a25f-1d9362c6bcd1", "images": ["Perception/single/410ee4bf-4ac3-40dc-a25f-1d9362c6bcd1_0.png"], "question": "Is there motion blur present in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "5cb98516-6817-456d-a891-a385208fd787", "images": ["Perception/single/5cb98516-6817-456d-a891-a385208fd787_0.png"], "question": "What category of distortion does this image belong to?\nA.haze\nB.dead pixel\nC.No distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "d14fceda-1f1b-4c63-9c3a-7c879b7453b1", "images": ["Perception/single/d14fceda-1f1b-4c63-9c3a-7c879b7453b1_0.png"], "question": "Is color distortion responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "7bffcdf0-16d0-4957-8a49-2f5ffc421265", "images": ["Perception/single/7bffcdf0-16d0-4957-8a49-2f5ffc421265_0.png"], "question": "Does image stretching obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "facee16d-f993-4cba-94de-ee0710c76759", "images": ["Perception/paired/facee16d-f993-4cba-94de-ee0710c76759_0.png", "Perception/paired/facee16d-f993-4cba-94de-ee0710c76759_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f99fd0f7-e522-4271-8ac5-7a15463d5015", "images": ["Perception/paired/f99fd0f7-e522-4271-8ac5-7a15463d5015_0.png", "Perception/paired/f99fd0f7-e522-4271-8ac5-7a15463d5015_1.png"], "question": "Which distortion category describes the changes from Image 1 to Image 2?\nA.noise\nB.dead pixel\nC.image compression\nD.No distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "d860629c-67ac-4877-8ace-7d314e44c00f", "images": ["Perception/single/d860629c-67ac-4877-8ace-7d314e44c00f_0.png"], "question": "Does image compression lead to information loss?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "c2d4770f-43f4-40e1-995b-804226608da0", "images": ["Perception/single/c2d4770f-43f4-40e1-995b-804226608da0_0.png"], "question": "Is deadline noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "145427a3-3eea-4501-9f0c-1d0d071aee6c", "images": ["Description/paired/145427a3-3eea-4501-9f0c-1d0d071aee6c_0.png", "Description/paired/145427a3-3eea-4501-9f0c-1d0d071aee6c_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe image compression artifacts, including blockiness, blurring, and loss of fine details, which significantly degrade the visual quality. Image 2 has no observable distortions and maintains clear and sharp details throughout. Therefore, Image 2 has higher overall quality due to its lack of distortions and preservation of detail.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "38b62a69-56f6-4d2c-9282-02a6d512253c", "images": ["Perception/paired/38b62a69-56f6-4d2c-9282-02a6d512253c_0.png", "Perception/paired/38b62a69-56f6-4d2c-9282-02a6d512253c_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5024ba17-d5d5-4c94-95b5-315254c7c49b", "images": ["Perception/single/5024ba17-d5d5-4c94-95b5-315254c7c49b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "f834a7de-daa1-4cc7-a81e-da25a32babbe", "images": ["Perception/paired/f834a7de-daa1-4cc7-a81e-da25a32babbe_0.png", "Perception/paired/f834a7de-daa1-4cc7-a81e-da25a32babbe_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable color distortion artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "79ed163e-22e8-43aa-87e4-a4415030f47f", "images": ["Perception/single/79ed163e-22e8-43aa-87e4-a4415030f47f_0.png"], "question": "Does dead pixel obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "665f707c-31d4-4b8e-a83f-b23f87c7c1d2", "images": ["Perception/single/665f707c-31d4-4b8e-a83f-b23f87c7c1d2_0.png"], "question": "Is there spatially correlated noise present in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "70debad1-0070-4368-8b97-fd5d9cb6ff1b", "images": ["Perception/single/70debad1-0070-4368-8b97-fd5d9cb6ff1b_0.png"], "question": "What category of distortion does this image belong to?\nA.dead pixel\nB.haze\nC.image compression\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "f7b5b8a0-4406-4610-9346-44ef341a13bd", "images": ["Perception/paired/f7b5b8a0-4406-4610-9346-44ef341a13bd_0.png", "Perception/paired/f7b5b8a0-4406-4610-9346-44ef341a13bd_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.missing tiles\nB.noise\nC.haze\nD.blur", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7c92e6ee-f95b-4350-8b14-348f18322079", "images": ["Perception/paired/7c92e6ee-f95b-4350-8b14-348f18322079_0.png", "Perception/paired/7c92e6ee-f95b-4350-8b14-348f18322079_1.png"], "question": "Does impulse noise affect the quality of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "7da44378-f1bb-45d8-b46f-f9e77d4848d5", "images": ["Perception/single/7da44378-f1bb-45d8-b46f-f9e77d4848d5_0.png"], "question": "What is the main cause of degradation in this image?\nA.noise\nB.image compression\nC.haze\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f7273e60-e44f-4a3e-a1b2-5d560cf8582d", "images": ["Perception/paired/f7273e60-e44f-4a3e-a1b2-5d560cf8582d_0.png", "Perception/paired/f7273e60-e44f-4a3e-a1b2-5d560cf8582d_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of image stretching?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "c85aeaca-c581-4e8e-ad8d-e98f76ed6116", "images": ["Perception/single/c85aeaca-c581-4e8e-ad8d-e98f76ed6116_0.png"], "question": "Can impulse noise and dead pixel be observed at the same time in this image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "46c40620-dabb-4cbf-a19c-b6822b45d3b2", "images": ["Perception/paired/46c40620-dabb-4cbf-a19c-b6822b45d3b2_0.png", "Perception/paired/46c40620-dabb-4cbf-a19c-b6822b45d3b2_1.png"], "question": "Which type of corruption is evident when comparing Image 2 against Image 1?\nA.image stretching\nB.image compression\nC.haze\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "22091b32-56cf-4b66-aa5c-105d9a055243", "images": ["Perception/single/22091b32-56cf-4b66-aa5c-105d9a055243_0.png"], "question": "Does impulse noise obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "69f9b534-defa-43c6-a418-6d62934f658d", "images": ["Perception/single/69f9b534-defa-43c6-a418-6d62934f658d_0.png"], "question": "What visual defect does this image exhibit?\nA.dead pixel\nB.cloud\nC.missing tiles\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "a7ad8dd9-dbea-4c87-a2c5-6e70b6db6458", "images": ["Perception/single/a7ad8dd9-dbea-4c87-a2c5-6e70b6db6458_0.png"], "question": "Does the image exhibit image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "157a440d-c7fc-4ecb-aaff-b4a5e2981e0d", "images": ["Perception/paired/157a440d-c7fc-4ecb-aaff-b4a5e2981e0d_0.png", "Perception/paired/157a440d-c7fc-4ecb-aaff-b4a5e2981e0d_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7ce1b2e9-6cb1-4043-ae73-37b7d842692e", "images": ["Perception/single/7ce1b2e9-6cb1-4043-ae73-37b7d842692e_0.png"], "question": "From the list, which artifacts can be observed in this scene?\nA. image compression\nB. impulse noise\nC. motion blur\nD. dead pixel", "answer": "A,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e6f6a318-9117-4417-bb7b-68429c3e7d06", "images": ["Perception/single/e6f6a318-9117-4417-bb7b-68429c3e7d06_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.striping\nB.sidelobe\nC.ghosting\nD.speckle", "answer": "D", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "8e4e224e-9335-4d3a-8e11-ae3fc58afb34", "images": ["Description/single/8e4e224e-9335-4d3a-8e11-ae3fc58afb34_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image stretching causes noticeable distortion, leading to uneven spatial distribution and unnatural elongation of features across the image. The texture and fine details of the surface are significantly degraded, making it difficult to discern patterns or identify specific elements such as clusters or boundaries. The image quality is poor, with reduced clarity and analytical usability.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "f46936f4-6e9a-4912-b15a-d35c5b552acd", "images": ["Description/single/f46936f4-6e9a-4912-b15a-d35c5b552acd_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe deadline noise introduces prominent horizontal lines across the image, disrupting the natural patterns and textures of the terrain. These artifacts obscure fine details, such as the clarity of ridges and valleys, making it difficult to interpret geographical features accurately. The image quality is poor, significantly impairing its usability for analytical purposes.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "c8f31b69-61d8-4a44-8381-af70d633ce1e", "images": ["Perception/paired/c8f31b69-61d8-4a44-8381-af70d633ce1e_0.png", "Perception/paired/c8f31b69-61d8-4a44-8381-af70d633ce1e_1.png"], "question": "How would you grade the distortion intensity affecting Image 2 relative to its reference counterpart?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a8255ad9-316f-463a-b820-1c41e84e00f6", "images": ["Perception/single/a8255ad9-316f-463a-b820-1c41e84e00f6_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.dead pixel\nB.image compression\nC.blur\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "eb4d9bfb-f037-4202-ac2f-0964be523f0e", "images": ["Perception/single/eb4d9bfb-f037-4202-ac2f-0964be523f0e_0.png"], "question": "Does cloud affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "86d49951-c8d6-4ece-8255-6bd379f6f248", "images": ["Perception/paired/86d49951-c8d6-4ece-8255-6bd379f6f248_0.png", "Perception/paired/86d49951-c8d6-4ece-8255-6bd379f6f248_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b5566e06-e3ad-4aa4-9d9b-5c9eafa731f8", "images": ["Perception/paired/b5566e06-e3ad-4aa4-9d9b-5c9eafa731f8_0.png", "Perception/paired/b5566e06-e3ad-4aa4-9d9b-5c9eafa731f8_1.png"], "question": "Assess the overall quality of Image 2 relative to Image 1 using the three labeled categories.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e702f4f4-312e-4bef-a6fb-339f6ef01c16", "images": ["Perception/paired/e702f4f4-312e-4bef-a6fb-339f6ef01c16_0.png", "Perception/paired/e702f4f4-312e-4bef-a6fb-339f6ef01c16_1.png"], "question": "Does image compression obscure details in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "d6d33f31-024d-4cdd-9d12-9169220bd750", "images": ["Perception/single/d6d33f31-024d-4cdd-9d12-9169220bd750_0.png"], "question": "Does this image contain gaussian noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "408d0869-b254-4e6d-bcd1-cf7963ff473f", "images": ["Perception/single/408d0869-b254-4e6d-bcd1-cf7963ff473f_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.image stretching\nB.dead pixel\nC.image compression\nD.blur", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "861ee2c0-eb9f-4188-855a-38465e426978", "images": ["Perception/single/861ee2c0-eb9f-4188-855a-38465e426978_0.png"], "question": "Is dead pixel responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "f9f0b56d-3a79-4695-9803-397382cc45c4", "images": ["Perception/paired/f9f0b56d-3a79-4695-9803-397382cc45c4_0.png", "Perception/paired/f9f0b56d-3a79-4695-9803-397382cc45c4_1.png"], "question": "Between the two images, does Image 2 display obvious distortion compared to Image 1?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ae04b3dc-6074-4804-af39-e34453001f3f", "images": ["Perception/single/ae04b3dc-6074-4804-af39-e34453001f3f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "a8910c6a-c9e1-4779-9e19-4472170806d5", "images": ["Perception/single/a8910c6a-c9e1-4779-9e19-4472170806d5_0.png"], "question": "Does gaussian blur lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "eab5694e-b0ea-4393-955e-2ee8cb0d0323", "images": ["Perception/paired/eab5694e-b0ea-4393-955e-2ee8cb0d0323_0.png", "Perception/paired/eab5694e-b0ea-4393-955e-2ee8cb0d0323_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.image stretching\nB.image compression\nC.haze\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "15a73eb8-5d18-40f2-b7ac-468b78fa3e7d", "images": ["Perception/single/15a73eb8-5d18-40f2-b7ac-468b78fa3e7d_0.png"], "question": "Is spatially correlated noise present and significant?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "cf533d21-34a5-4a03-8f89-e949f555fa87", "images": ["Perception/single/cf533d21-34a5-4a03-8f89-e949f555fa87_0.png"], "question": "What form of distortion is most apparent here?\nA.dead pixel\nB.No distortion\nC.haze\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "b700a544-3f0c-446d-823d-e08f7655dcb1", "images": ["Perception/paired/b700a544-3f0c-446d-823d-e08f7655dcb1_0.png", "Perception/paired/b700a544-3f0c-446d-823d-e08f7655dcb1_1.png"], "question": "Considering Image 1 as ground truth, what is the distortion severity rating for Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b30be7df-31f9-4e06-af87-0912f34ca19b", "images": ["Perception/single/b30be7df-31f9-4e06-af87-0912f34ca19b_0.png"], "question": "Does image stretching lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "0efecf96-c254-493d-b7f8-50e291a52cc8", "images": ["Perception/single/0efecf96-c254-493d-b7f8-50e291a52cc8_0.png"], "question": "Does image compression interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "51a437e1-e711-40bd-9b4a-2d0fce09aa52", "images": ["Perception/paired/51a437e1-e711-40bd-9b4a-2d0fce09aa52_0.png", "Perception/paired/51a437e1-e711-40bd-9b4a-2d0fce09aa52_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "a92691d1-1f6b-4c09-b9e0-a87676c5e7a0", "images": ["Perception/single/a92691d1-1f6b-4c09-b9e0-a87676c5e7a0_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.dead pixel\nB.haze\nC.blur\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "0accd552-e939-4900-bf2f-dcaa4f39840a", "images": ["Description/paired/0accd552-e939-4900-bf2f-dcaa4f39840a_0.png", "Description/paired/0accd552-e939-4900-bf2f-dcaa4f39840a_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains severe dead pixel artifacts, appearing as a dense, noisy pattern that obscures any meaningful content. Therefore, Image 1 has higher overall quality due to the absence of distortions and the clear visibility of details.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "ead345b6-7b55-4915-98f1-ab65eee9f162", "images": ["Perception/single/ead345b6-7b55-4915-98f1-ab65eee9f162_0.png"], "question": "Does impulse noise lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "902f0d6d-23ac-4412-87a0-b6a55ca3df17", "images": ["Description/single/902f0d6d-23ac-4412-87a0-b6a55ca3df17_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe color distortion causes unnatural green hues to dominate the image, altering the appearance of vegetation and built structures.  \nThe distortion obscures the differentiation between land cover types, making it difficult to identify roads, buildings, and natural features accurately.  \nThe image quality is poor, significantly limiting its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "f59a4ca3-f5f1-4246-9e3c-5ca36b4a9349", "images": ["Perception/single/f59a4ca3-f5f1-4246-9e3c-5ca36b4a9349_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.striping\nC.speckle\nD.ghosting", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "b68e859a-b36a-4d49-a9b5-6b8a010edab5", "images": ["Perception/paired/b68e859a-b36a-4d49-a9b5-6b8a010edab5_0.png", "Perception/paired/b68e859a-b36a-4d49-a9b5-6b8a010edab5_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.No distortion\nB.color distortion\nC.cloud\nD.dead pixel", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "289e318e-e829-4ee3-83ba-a6b92f36a680", "images": ["Perception/paired/289e318e-e829-4ee3-83ba-a6b92f36a680_0.png", "Perception/paired/289e318e-e829-4ee3-83ba-a6b92f36a680_1.png"], "question": "Which distortion most clearly appears in the degraded image?\nA.No distortion\nB.image compression\nC.color distortion\nD.noise", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "dcd1f0c8-93c5-4448-b991-a3e84d1b9aba", "images": ["Perception/single/dcd1f0c8-93c5-4448-b991-a3e84d1b9aba_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "e1c04772-81e1-4afe-87c2-28bd32eb422b", "images": ["Description/paired/e1c04772-81e1-4afe-87c2-28bd32eb422b_0.png", "Description/paired/e1c04772-81e1-4afe-87c2-28bd32eb422b_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong color distortion, with an unnatural pink hue dominating the entire scene, making it difficult to discern natural features accurately. Image 2 shows no observable distortions and presents a natural color balance with clear and distinct features. Therefore, Image 2 has higher overall quality due to its accurate color representation and lack of visual artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "c600b1dc-8a08-4e9c-901d-73ce95ead440", "images": ["Perception/single/c600b1dc-8a08-4e9c-901d-73ce95ead440_0.png"], "question": "Is spatially correlated noise present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "2df38d43-5265-4ccd-ab06-4cfd45ae3932", "images": ["Perception/single/2df38d43-5265-4ccd-ab06-4cfd45ae3932_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.dead pixel\nB.image stretching\nC.blur\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "2d36d3b6-6cac-488b-acab-d337d572cd6c", "images": ["Description/paired/2d36d3b6-6cac-488b-acab-d337d572cd6c_0.png", "Description/paired/2d36d3b6-6cac-488b-acab-d337d572cd6c_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains strong dead pixel artifacts, appearing as numerous white specks scattered across the entire image. Image 2 has no observable distortions and appears clean and high-quality. Therefore, Image 2 has higher overall quality due to the absence of any visible artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "b1b26aab-2294-4b91-9196-273ef7ea87ca", "images": ["Perception/single/b1b26aab-2294-4b91-9196-273ef7ea87ca_0.png"], "question": "Is gaussian noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "3e4d914c-a7ad-4f05-94d1-812b22226284", "images": ["Perception/single/3e4d914c-a7ad-4f05-94d1-812b22226284_0.png"], "question": "Is the image impacted by missing tiles?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "82126438-f963-41c5-baaf-2e92afed3b1a", "images": ["Perception/single/82126438-f963-41c5-baaf-2e92afed3b1a_0.png"], "question": "Can dead pixel be observed in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "5cf97855-16f7-4c9d-9ce6-4d33e8e5b925", "images": ["Perception/single/5cf97855-16f7-4c9d-9ce6-4d33e8e5b925_0.png"], "question": "What is the dominant distortion in this image?\nA.No distortion\nB.noise\nC.haze\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "187f1c0a-827e-4ae7-96a7-93b4f5f55bd6", "images": ["Perception/single/187f1c0a-827e-4ae7-96a7-93b4f5f55bd6_0.png"], "question": "Is image stretching visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "59990b18-577b-403f-8158-785d8fa6494b", "images": ["Description/single/59990b18-577b-403f-8158-785d8fa6494b_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe stripe noise creates prominent horizontal bands that disrupt the uniformity of the image, making building edges and fine details appear fragmented and unclear. The distortion obscures critical features such as road layouts and vegetation patterns, significantly reducing the ability to interpret spatial relationships and land use. The image quality is poor, with substantial degradation impacting its usability for analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "2649ad8a-b3d6-4c11-98a8-c0ec4b2a8c5d", "images": ["Perception/paired/2649ad8a-b3d6-4c11-98a8-c0ec4b2a8c5d_0.png", "Perception/paired/2649ad8a-b3d6-4c11-98a8-c0ec4b2a8c5d_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "bd42cff7-d9c4-4cfe-a273-b0404c76df06", "images": ["Perception/paired/bd42cff7-d9c4-4cfe-a273-b0404c76df06_0.png", "Perception/paired/bd42cff7-d9c4-4cfe-a273-b0404c76df06_1.png"], "question": "Assess the distortion level in Image 2 relative to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "190e3c10-3cd6-403f-9fc6-a5b16e1367f3", "images": ["Perception/single/190e3c10-3cd6-403f-9fc6-a5b16e1367f3_0.png"], "question": "Are image compression and motion blur present together in the scene?\nA.No\nB.Yes", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "8b7bee95-05e8-4a4b-819c-c5a291119312", "images": ["Perception/single/8b7bee95-05e8-4a4b-819c-c5a291119312_0.png"], "question": "From the list, which artifacts can be observed in this scene?\nA. deadline noise\nB. haze\nC. dead pixel\nD. image stretching", "answer": "C,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "3a804cba-8ffc-47c6-b1a0-37886d5d76cc", "images": ["Perception/single/3a804cba-8ffc-47c6-b1a0-37886d5d76cc_0.png"], "question": "Are deadline noise and missing tiles present together in the scene?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "d3552b0e-5d82-4bd6-896e-b3fb4b193b80", "images": ["Perception/paired/d3552b0e-5d82-4bd6-896e-b3fb4b193b80_0.png", "Perception/paired/d3552b0e-5d82-4bd6-896e-b3fb4b193b80_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "01f79946-4f1d-404a-88f8-e3a460968bf2", "images": ["Description/paired/01f79946-4f1d-404a-88f8-e3a460968bf2_0.png", "Description/paired/01f79946-4f1d-404a-88f8-e3a460968bf2_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong image compression artifacts, including blockiness and blurring, which significantly degrade the visual clarity and detail. Image 2 shows no observable distortions and maintains clear and sharp details throughout. Therefore, Image 2 has higher overall quality due to the absence of distortions and better visual clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "4c5c9ee7-37f2-4b44-8d23-94ec9ad084c9", "images": ["Perception/single/4c5c9ee7-37f2-4b44-8d23-94ec9ad084c9_0.png"], "question": "What category of distortion does this image belong to?\nA.blur\nB.image compression\nC.noise\nD.missing tiles", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "692d73f0-c886-4b4c-bbac-eb57ac5145b3", "images": ["Perception/single/692d73f0-c886-4b4c-bbac-eb57ac5145b3_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.image stretching\nB.dead pixel\nC.blur\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "462dab5a-6120-4506-826e-7c84a47ae1b5", "images": ["Perception/paired/462dab5a-6120-4506-826e-7c84a47ae1b5_0.png", "Perception/paired/462dab5a-6120-4506-826e-7c84a47ae1b5_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cf90f13d-4319-42f0-9297-32a1bc7fb70b", "images": ["Perception/single/cf90f13d-4319-42f0-9297-32a1bc7fb70b_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "558b6058-3e77-4503-b264-7ad61f15dc13", "images": ["Perception/single/558b6058-3e77-4503-b264-7ad61f15dc13_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.color distortion\nC.image stretching\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "d76628d0-377b-49bf-9a6f-4785fef6dea3", "images": ["Perception/paired/d76628d0-377b-49bf-9a6f-4785fef6dea3_0.png", "Perception/paired/d76628d0-377b-49bf-9a6f-4785fef6dea3_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.blur\nB.noise\nC.image stretching\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "14014a2d-d7e8-4947-b71d-cbb1da096c04", "images": ["Perception/paired/14014a2d-d7e8-4947-b71d-cbb1da096c04_0.png", "Perception/paired/14014a2d-d7e8-4947-b71d-cbb1da096c04_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of haze?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "54b18c51-df27-40ae-bf2b-d9d55abbf260", "images": ["Perception/single/54b18c51-df27-40ae-bf2b-d9d55abbf260_0.png"], "question": "Does dead pixel obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "e7381be3-1c5e-40ae-a056-c1fc67188766", "images": ["Perception/single/e7381be3-1c5e-40ae-a056-c1fc67188766_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.noise\nB.color distortion\nC.image stretching\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "31556af5-f610-4394-b783-61dcbc9a4e0f", "images": ["Perception/single/31556af5-f610-4394-b783-61dcbc9a4e0f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "b3523604-76ff-4f80-9cba-ca7e4a5e3455", "images": ["Perception/single/b3523604-76ff-4f80-9cba-ca7e4a5e3455_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "1d2cd177-4b4a-49c7-902b-5e0d8ec8feaa", "images": ["Perception/single/1d2cd177-4b4a-49c7-902b-5e0d8ec8feaa_0.png"], "question": "Does this image contain color distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "6304c145-7a01-4c1f-8e8b-70e837a9477a", "images": ["Perception/paired/6304c145-7a01-4c1f-8e8b-70e837a9477a_0.png", "Perception/paired/6304c145-7a01-4c1f-8e8b-70e837a9477a_1.png"], "question": "Assess the overall quality of Image 2 relative to Image 1 using the three labeled categories.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6e986e36-0f5e-40f5-9732-6d61cb466069", "images": ["Perception/single/6e986e36-0f5e-40f5-9732-6d61cb466069_0.png"], "question": "Does image compression compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "3f0fad8e-47a0-4744-90b6-e232fb90248c", "images": ["Perception/single/3f0fad8e-47a0-4744-90b6-e232fb90248c_0.png"], "question": "What category of distortion does this image belong to?\nA.blur\nB.image compression\nC.noise\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "dc6f1a7a-b075-4810-baec-d74f5a4ef843", "images": ["Perception/single/dc6f1a7a-b075-4810-baec-d74f5a4ef843_0.png"], "question": "Is image compression a critical issue in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "6cc4954d-35ab-42ec-9fa9-b463e4985d13", "images": ["Perception/paired/6cc4954d-35ab-42ec-9fa9-b463e4985d13_0.png", "Perception/paired/6cc4954d-35ab-42ec-9fa9-b463e4985d13_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.No distortion\nB.cloud\nC.noise\nD.image compression", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "63cfc923-5a1b-4d72-9195-bb5f29daec6d", "images": ["Perception/single/63cfc923-5a1b-4d72-9195-bb5f29daec6d_0.png"], "question": "Does this image contain motion blur?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "8289808b-59be-4d64-8779-8d6aa29edb14", "images": ["Perception/single/8289808b-59be-4d64-8779-8d6aa29edb14_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.ghosting\nC.sidelobe\nD.striping", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "18cf2b9a-9d76-47cb-b835-20936578358c", "images": ["Description/single/18cf2b9a-9d76-47cb-b835-20936578358c_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The color distortion introduces unnatural hues, causing vegetation and urban areas to appear less realistic and visually inconsistent.  \nThe altered color tones obscure fine details in vegetation and building materials, reducing the ability to distinguish land cover types and structural features.  \nThe image quality is moderately degraded, impacting its utility for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "94a63be0-301a-4973-9090-0abff03672d6", "images": ["Perception/paired/94a63be0-301a-4973-9090-0abff03672d6_0.png", "Perception/paired/94a63be0-301a-4973-9090-0abff03672d6_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.haze\nB.No distortion\nC.color distortion\nD.image compression", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5d79ccc1-9b15-412a-97a3-a92dcf82d4fa", "images": ["Perception/single/5d79ccc1-9b15-412a-97a3-a92dcf82d4fa_0.png"], "question": "Is there speckle noise present in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "b946dbe8-4ef8-483c-ac27-66c7594d4583", "images": ["Perception/single/b946dbe8-4ef8-483c-ac27-66c7594d4583_0.jpg"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.striping\nC.sidelobe\nD.ghosting", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "2427517d-55b9-4645-a6db-3e9f2947c4ea", "images": ["Perception/paired/2427517d-55b9-4645-a6db-3e9f2947c4ea_0.png", "Perception/paired/2427517d-55b9-4645-a6db-3e9f2947c4ea_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.No distortion\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0d5cfbc8-fcc7-4c91-88cd-6c8f637d0dba", "images": ["Perception/single/0d5cfbc8-fcc7-4c91-88cd-6c8f637d0dba_0.png"], "question": "Identify the main type of corruption in this image.\nA.haze\nB.blur\nC.No distortion\nD.cloud", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "1dce264f-8840-406a-a140-f0d026e91007", "images": ["Perception/single/1dce264f-8840-406a-a140-f0d026e91007_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.ghosting\nB.striping\nC.speckle\nD.sidelobe", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "17860ecc-f34c-4576-8f16-ff828bcf5862", "images": ["Perception/single/17860ecc-f34c-4576-8f16-ff828bcf5862_0.png"], "question": "Does the image exhibit dead pixel?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "a1ca8fa5-76a9-43b4-912a-90f2f60dfc41", "images": ["Perception/paired/a1ca8fa5-76a9-43b4-912a-90f2f60dfc41_0.png", "Perception/paired/a1ca8fa5-76a9-43b4-912a-90f2f60dfc41_1.png"], "question": "Given that Image 1 is the reference and Image 2 is distorted, how severe is the degradation in Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "61735922-1865-4bb0-86e8-0e13cf9e9b8d", "images": ["Perception/single/61735922-1865-4bb0-86e8-0e13cf9e9b8d_0.png"], "question": "What is the primary distortion type in this image?\nA.haze\nB.cloud\nC.image stretching\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "dbdd0c43-2719-42bb-8feb-4c4435c52d8c", "images": ["Perception/single/dbdd0c43-2719-42bb-8feb-4c4435c52d8c_0.png"], "question": "Does cloud interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "0ac2806d-1056-4bbf-94b4-6819ff5ae324", "images": ["Perception/single/0ac2806d-1056-4bbf-94b4-6819ff5ae324_0.png"], "question": "Does image compression result in missing information?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "d0621911-fc49-46d7-ab6f-ed9d66490721", "images": ["Perception/paired/d0621911-fc49-46d7-ab6f-ed9d66490721_0.png", "Perception/paired/d0621911-fc49-46d7-ab6f-ed9d66490721_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable dead pixel artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b49b0fbd-3488-4bec-b862-7e1bc2d5950c", "images": ["Perception/single/b49b0fbd-3488-4bec-b862-7e1bc2d5950c_0.png"], "question": "Does gaussian noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "096580a6-ffec-443d-b9d1-f6866ce211f8", "images": ["Perception/paired/096580a6-ffec-443d-b9d1-f6866ce211f8_0.png", "Perception/paired/096580a6-ffec-443d-b9d1-f6866ce211f8_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a2996198-3b59-403a-8be5-8b86bf7537c8", "images": ["Perception/paired/a2996198-3b59-403a-8be5-8b86bf7537c8_0.png", "Perception/paired/a2996198-3b59-403a-8be5-8b86bf7537c8_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d132eb91-1d6c-4820-b3eb-7f168436f2b6", "images": ["Perception/single/d132eb91-1d6c-4820-b3eb-7f168436f2b6_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "99e70a2c-8aa3-4d6d-8c07-b74cc921bf25", "images": ["Perception/paired/99e70a2c-8aa3-4d6d-8c07-b74cc921bf25_0.png", "Perception/paired/99e70a2c-8aa3-4d6d-8c07-b74cc921bf25_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable motion blur artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3aa51ab7-4860-45ca-adfd-e0e74de2c6df", "images": ["Perception/single/3aa51ab7-4860-45ca-adfd-e0e74de2c6df_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.cloud\nB.No distortion\nC.image compression\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "0c001899-e0eb-446d-bf1e-1712b31e428a", "images": ["Perception/single/0c001899-e0eb-446d-bf1e-1712b31e428a_0.png"], "question": "Can cloud be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "c05e81fe-1ced-468a-8869-850371eec8f8", "images": ["Perception/single/c05e81fe-1ced-468a-8869-850371eec8f8_0.png"], "question": "Is sidelobe interference a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f80a2c64-c169-45fa-9a83-f0fa85a0b7ea", "images": ["Perception/single/f80a2c64-c169-45fa-9a83-f0fa85a0b7ea_0.png"], "question": "Can dead pixel and impulse noise be observed at the same time in this image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "c260f882-5724-46f9-a302-b20c88630ffb", "images": ["Perception/single/c260f882-5724-46f9-a302-b20c88630ffb_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.No distortion\nB.image compression\nC.cloud\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "dead4581-0642-4a1c-a181-adba97d58698", "images": ["Perception/single/dead4581-0642-4a1c-a181-adba97d58698_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.blur\nC.cloud\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "d9fae953-48b4-4407-87c9-9fa2e9a84fb7", "images": ["Perception/single/d9fae953-48b4-4407-87c9-9fa2e9a84fb7_0.png"], "question": "What form of distortion is most apparent here?\nA.dead pixel\nB.color distortion\nC.blur\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "38453ff7-2d9a-40c2-a715-e34e1343121b", "images": ["Perception/single/38453ff7-2d9a-40c2-a715-e34e1343121b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "77e928d4-5c12-4d85-962c-4a51afc1d262", "images": ["Perception/single/77e928d4-5c12-4d85-962c-4a51afc1d262_0.png"], "question": "What is the main cause of degradation in this image?\nA.image compression\nB.haze\nC.noise\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "34ba55a3-2899-44ba-8c39-3945e2e70d15", "images": ["Perception/paired/34ba55a3-2899-44ba-8c39-3945e2e70d15_0.png", "Perception/paired/34ba55a3-2899-44ba-8c39-3945e2e70d15_1.png"], "question": "How would you grade the distortion intensity affecting Image 2 relative to its reference counterpart?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fab58a3c-6d82-47f6-a69c-6e0278907f3a", "images": ["Perception/single/fab58a3c-6d82-47f6-a69c-6e0278907f3a_0.png"], "question": "Is missing tiles a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "cfe22eef-f400-42ff-af9b-429ace833ade", "images": ["Perception/paired/cfe22eef-f400-42ff-af9b-429ace833ade_0.png", "Perception/paired/cfe22eef-f400-42ff-af9b-429ace833ade_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.noise\nB.image compression\nC.haze\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ed8259fd-6ad0-4e48-bd8f-0f116cd0501a", "images": ["Perception/paired/ed8259fd-6ad0-4e48-bd8f-0f116cd0501a_0.png", "Perception/paired/ed8259fd-6ad0-4e48-bd8f-0f116cd0501a_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.No distortion\nB.image compression\nC.haze\nD.color distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "17d860e0-a658-4b9a-ac62-1c9913c86811", "images": ["Perception/single/17d860e0-a658-4b9a-ac62-1c9913c86811_0.png"], "question": "Is the image impacted by image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "e67adf7e-058d-4dcd-8513-f22e623de1c8", "images": ["Perception/paired/e67adf7e-058d-4dcd-8513-f22e623de1c8_0.png", "Perception/paired/e67adf7e-058d-4dcd-8513-f22e623de1c8_1.png"], "question": "Considering Image 1 as ground truth, what is the distortion severity rating for Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "01bb6762-4b76-4d02-99ac-322335317f4b", "images": ["Perception/paired/01bb6762-4b76-4d02-99ac-322335317f4b_0.png", "Perception/paired/01bb6762-4b76-4d02-99ac-322335317f4b_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.missing tiles\nB.cloud\nC.No distortion\nD.dead pixel", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "850d6cab-5a52-4062-832a-eb715098026b", "images": ["Perception/single/850d6cab-5a52-4062-832a-eb715098026b_0.png"], "question": "Does color distortion obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "dd65d054-6b78-4806-a4e3-d9aa11569118", "images": ["Perception/single/dd65d054-6b78-4806-a4e3-d9aa11569118_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "3689e9a8-ca9f-4b55-8b35-4f91a2d61a82", "images": ["Perception/single/3689e9a8-ca9f-4b55-8b35-4f91a2d61a82_0.png"], "question": "Can haze be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "a5d3c94c-88b2-42a3-80bb-769d52b8b012", "images": ["Description/paired/a5d3c94c-88b2-42a3-80bb-769d52b8b012_0.png", "Description/paired/a5d3c94c-88b2-42a3-80bb-769d52b8b012_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains moderate cloud artifacts that obscure parts of the underlying terrain, making it difficult to discern details. Image 2 has no observable distortions and presents a clear view of the terrain. Therefore, Image 2 has higher overall quality due to its clarity and lack of cloud artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "7e1d4985-78a0-45d1-aaaa-973ea4be42ed", "images": ["Perception/single/7e1d4985-78a0-45d1-aaaa-973ea4be42ed_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "f82add15-1d4f-47e4-b18f-ddcf5b75d347", "images": ["Perception/single/f82add15-1d4f-47e4-b18f-ddcf5b75d347_0.png"], "question": "Does cloud lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "d81dd45d-7b4a-4bff-9bed-71e8beeb0b02", "images": ["Perception/single/d81dd45d-7b4a-4bff-9bed-71e8beeb0b02_0.png"], "question": "Does sidelobe interference lead to information loss?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "c80980c4-ab19-46f2-9569-f1b8ca019728", "images": ["Perception/single/c80980c4-ab19-46f2-9569-f1b8ca019728_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "ee501cbc-ce65-463c-82a9-4f4dfc165dd9", "images": ["Perception/paired/ee501cbc-ce65-463c-82a9-4f4dfc165dd9_0.png", "Perception/paired/ee501cbc-ce65-463c-82a9-4f4dfc165dd9_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d49b9f08-457c-48e3-b38a-7fc877e4d41d", "images": ["Perception/paired/d49b9f08-457c-48e3-b38a-7fc877e4d41d_0.png", "Perception/paired/d49b9f08-457c-48e3-b38a-7fc877e4d41d_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of color distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3045c33b-81df-4630-8c92-9cadac27d532", "images": ["Perception/single/3045c33b-81df-4630-8c92-9cadac27d532_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.missing tiles\nB.color distortion\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "3e462e05-de36-4222-93f6-99601515576b", "images": ["Perception/single/3e462e05-de36-4222-93f6-99601515576b_0.png"], "question": "What distortion is present in the image?\nA.image compression\nB.missing tiles\nC.image stretching\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "b80c59f0-6188-4199-af68-6af3095096bd", "images": ["Perception/single/b80c59f0-6188-4199-af68-6af3095096bd_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.speckle\nC.ghosting\nD.striping", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "3caf5629-f1a8-4142-bca3-892eb4e2eb07", "images": ["Perception/single/3caf5629-f1a8-4142-bca3-892eb4e2eb07_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.cloud\nB.image compression\nC.noise\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "59633c28-06d8-4437-a689-8f1557b91225", "images": ["Perception/paired/59633c28-06d8-4437-a689-8f1557b91225_0.png", "Perception/paired/59633c28-06d8-4437-a689-8f1557b91225_1.png"], "question": "What is the severity of the artifact in Image 2 when compared to Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "42f5c7df-af82-4ddf-a142-79ff7e454f76", "images": ["Perception/single/42f5c7df-af82-4ddf-a142-79ff7e454f76_0.png"], "question": "What visual defect does this image exhibit?\nA.noise\nB.cloud\nC.blur\nD.dead pixel", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "88c4cffc-5526-4e2a-b8b8-9ddd8f52779d", "images": ["Perception/single/88c4cffc-5526-4e2a-b8b8-9ddd8f52779d_0.png"], "question": "What form of distortion is most apparent here?\nA.image compression\nB.No distortion\nC.haze\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "9e7103b9-c33e-4593-9358-11843c92b0ce", "images": ["Perception/single/9e7103b9-c33e-4593-9358-11843c92b0ce_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "520ba8b9-8bed-4dbc-9011-e07261b2d5be", "images": ["Perception/paired/520ba8b9-8bed-4dbc-9011-e07261b2d5be_0.png", "Perception/paired/520ba8b9-8bed-4dbc-9011-e07261b2d5be_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5f77fe3a-2194-4c92-a618-08628c18685e", "images": ["Perception/paired/5f77fe3a-2194-4c92-a618-08628c18685e_0.png", "Perception/paired/5f77fe3a-2194-4c92-a618-08628c18685e_1.png"], "question": "How much quality degradation do you observe in the distorted image versus the reference?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cc8fd051-48fd-483b-93a2-bdb2a002b1ad", "images": ["Perception/single/cc8fd051-48fd-483b-93a2-bdb2a002b1ad_0.png"], "question": "What category of distortion does this image belong to?\nA.dead pixel\nB.No distortion\nC.image compression\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "b4a7c9a4-445c-4ffc-aed9-5acb2c2a4e89", "images": ["Perception/paired/b4a7c9a4-445c-4ffc-aed9-5acb2c2a4e89_0.png", "Perception/paired/b4a7c9a4-445c-4ffc-aed9-5acb2c2a4e89_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f9ab2b50-6415-4e83-a7e4-cbdd13079250", "images": ["Perception/single/f9ab2b50-6415-4e83-a7e4-cbdd13079250_0.png"], "question": "What category of distortion does this image belong to?\nA.cloud\nB.noise\nC.missing tiles\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "ddfa3775-0f7e-46d0-a403-d2d90fa6930a", "images": ["Perception/single/ddfa3775-0f7e-46d0-a403-d2d90fa6930a_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.blur\nC.image stretching\nD.dead pixel", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "850f27c5-60c8-4213-8f99-398b0fad91b4", "images": ["Perception/single/850f27c5-60c8-4213-8f99-398b0fad91b4_0.png"], "question": "Select all types of distortions affecting this image.\nA. color distortion\nB. dead pixel\nC. gaussian blur\nD. stripe noise", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "60a4e016-dcc4-4d4e-9f01-2e8ae409beab", "images": ["Description/single/60a4e016-dcc4-4d4e-9f01-2e8ae409beab_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe dead pixel distortion introduces a dense, noisy texture that obscures fine details and disrupts the natural patterns of the landscape. Key features such as roads, buildings, and vegetation are indistinguishable, significantly reducing the ability to interpret spatial relationships and land use. The image quality is extremely poor, making it unsuitable for analytical or visual purposes.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "644612ae-6379-4cec-9eb0-70626b315a7e", "images": ["Perception/single/644612ae-6379-4cec-9eb0-70626b315a7e_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "8d0769a4-7e0f-4fa3-8877-5930b278506c", "images": ["Perception/single/8d0769a4-7e0f-4fa3-8877-5930b278506c_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "ba8cdab8-69c5-4583-806f-8e1c8b975cb0", "images": ["Perception/single/ba8cdab8-69c5-4583-806f-8e1c8b975cb0_0.png"], "question": "Is dead pixel the main factor in this distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "d3c29ed2-d567-47d9-aff0-1eba38556322", "images": ["Description/paired/d3c29ed2-d567-47d9-aff0-1eba38556322_0.png", "Description/paired/d3c29ed2-d567-47d9-aff0-1eba38556322_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains strong dead pixel artifacts, appearing as numerous white and black specks scattered across the entire image, which significantly degrade its visual quality. Image 2 has no observable distortions and maintains clear and consistent visual details throughout. Therefore, Image 2 has higher overall quality due to the absence of any distortions compared to the heavily artifacted Image 1.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "408f331e-c279-4c22-9772-1df69b72d615", "images": ["Perception/single/408f331e-c279-4c22-9772-1df69b72d615_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "cac4552a-6a3b-400c-94e0-4f2fde71d2b0", "images": ["Perception/single/cac4552a-6a3b-400c-94e0-4f2fde71d2b0_0.png"], "question": "Does sidelobe interference compromise the data integrity?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "29d4cd18-597c-41fb-9bab-b388e1d28f55", "images": ["Description/paired/29d4cd18-597c-41fb-9bab-b388e1d28f55_0.png", "Description/paired/29d4cd18-597c-41fb-9bab-b388e1d28f55_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually sharp and clear. Image 2 contains strong Gaussian blur artifacts, making the details appear smeared and less distinct. Therefore, Image 1 has higher overall quality due to its clarity and lack of distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "95546c1e-a371-41cf-bc07-928bb84d7792", "images": ["Perception/single/95546c1e-a371-41cf-bc07-928bb84d7792_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.ghosting\nC.striping\nD.speckle", "answer": "D", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "a8abf5d7-b5eb-4267-95fd-6c79e0312f57", "images": ["Perception/paired/a8abf5d7-b5eb-4267-95fd-6c79e0312f57_0.png", "Perception/paired/a8abf5d7-b5eb-4267-95fd-6c79e0312f57_1.png"], "question": "Given that Image 1 is the reference and Image 2 is distorted, how severe is the degradation in Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "54097d39-9eed-4baf-b239-951583c27c6c", "images": ["Perception/paired/54097d39-9eed-4baf-b239-951583c27c6c_0.png", "Perception/paired/54097d39-9eed-4baf-b239-951583c27c6c_1.png"], "question": "Compare Image 2 to Image 1 and choose the severity of distortion.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "589d2a1e-4cc3-419f-9a89-c38f0928c63e", "images": ["Perception/single/589d2a1e-4cc3-419f-9a89-c38f0928c63e_0.png"], "question": "Does color distortion reduce the usability of the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "d30ee1c3-5959-416a-a90b-1c4e5bd34048", "images": ["Perception/single/d30ee1c3-5959-416a-a90b-1c4e5bd34048_0.png"], "question": "Does image compression affect the image quality?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "4e469c41-e015-4c36-af2c-8d65017c693c", "images": ["Perception/single/4e469c41-e015-4c36-af2c-8d65017c693c_0.png"], "question": "Is spatially correlated noise present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "e5327fd2-5131-4031-9b17-e5501d01b904", "images": ["Perception/paired/e5327fd2-5131-4031-9b17-e5501d01b904_0.png", "Perception/paired/e5327fd2-5131-4031-9b17-e5501d01b904_1.png"], "question": "How would you rate the degradation severity in Image 2 compared to the reference Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "888b6061-9f03-4b17-8ded-d899cac5b25c", "images": ["Perception/paired/888b6061-9f03-4b17-8ded-d899cac5b25c_0.png", "Perception/paired/888b6061-9f03-4b17-8ded-d899cac5b25c_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0ccb04ae-9c96-4ed6-b633-5ddfd597de09", "images": ["Perception/single/0ccb04ae-9c96-4ed6-b633-5ddfd597de09_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "ab0ca835-a999-47a5-a34d-374c93cf98ba", "images": ["Perception/paired/ab0ca835-a999-47a5-a34d-374c93cf98ba_0.png", "Perception/paired/ab0ca835-a999-47a5-a34d-374c93cf98ba_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "8e11b5e6-1166-4f06-9ea5-6017d8517f9e", "images": ["Perception/single/8e11b5e6-1166-4f06-9ea5-6017d8517f9e_0.png"], "question": "What category of distortion does this image belong to?\nA.image stretching\nB.image compression\nC.cloud\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "b56fa146-c0bf-413b-9cd3-6f606334932b", "images": ["Perception/paired/b56fa146-c0bf-413b-9cd3-6f606334932b_0.png", "Perception/paired/b56fa146-c0bf-413b-9cd3-6f606334932b_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "79215431-78f7-4e2a-8e43-6d6bdddaee43", "images": ["Perception/single/79215431-78f7-4e2a-8e43-6d6bdddaee43_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.dead pixel\nB.haze\nC.noise\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "642c404a-4d22-40d4-a81a-70208bf6c46a", "images": ["Perception/paired/642c404a-4d22-40d4-a81a-70208bf6c46a_0.png", "Perception/paired/642c404a-4d22-40d4-a81a-70208bf6c46a_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.image compression\nB.image stretching\nC.dead pixel\nD.blur", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "7160e68f-473d-4f7f-82b5-a5868e50fa6f", "images": ["Perception/single/7160e68f-473d-4f7f-82b5-a5868e50fa6f_0.png"], "question": "What is the dominant distortion in this image?\nA.image stretching\nB.blur\nC.No distortion\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "e2f9c696-6582-4e4c-afc7-985ead23c95c", "images": ["Perception/paired/e2f9c696-6582-4e4c-afc7-985ead23c95c_0.png", "Perception/paired/e2f9c696-6582-4e4c-afc7-985ead23c95c_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of motion blur?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "994b55fb-3e61-40fa-9dea-34278fb63c0f", "images": ["Perception/paired/994b55fb-3e61-40fa-9dea-34278fb63c0f_0.png", "Perception/paired/994b55fb-3e61-40fa-9dea-34278fb63c0f_1.png"], "question": "Does motion blur reduce the usability of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "9913417d-b06e-47a5-bcbb-6c30efa3666c", "images": ["Perception/paired/9913417d-b06e-47a5-bcbb-6c30efa3666c_0.png", "Perception/paired/9913417d-b06e-47a5-bcbb-6c30efa3666c_1.png"], "question": "Comparing Image 1 (reference) and Image 2 (degraded), what distortion best explains the difference?\nA.color distortion\nB.image compression\nC.No distortion\nD.missing tiles", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e91aadfc-e990-471a-a251-5f511905bc19", "images": ["Perception/single/e91aadfc-e990-471a-a251-5f511905bc19_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "2dd8ffb6-8d66-42b8-87fa-657036e2970a", "images": ["Perception/paired/2dd8ffb6-8d66-42b8-87fa-657036e2970a_0.png", "Perception/paired/2dd8ffb6-8d66-42b8-87fa-657036e2970a_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.color distortion\nB.haze\nC.missing tiles\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "2ef7ae9d-f857-4f9c-9b46-c86bb5efed36", "images": ["Perception/paired/2ef7ae9d-f857-4f9c-9b46-c86bb5efed36_0.png", "Perception/paired/2ef7ae9d-f857-4f9c-9b46-c86bb5efed36_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.color distortion\nC.noise\nD.missing tiles", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e86ca583-7f7e-4fb6-98fe-88421e626cdb", "images": ["Perception/single/e86ca583-7f7e-4fb6-98fe-88421e626cdb_0.png"], "question": "Is spatially correlated noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "46b9b524-acf4-453e-989f-8f2e4ca6fdb7", "images": ["Perception/single/46b9b524-acf4-453e-989f-8f2e4ca6fdb7_0.png"], "question": "Which distortion most significantly affects this image?\nA.cloud\nB.blur\nC.color distortion\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "78850f87-56e1-4d63-9618-7b549eee254f", "images": ["Description/paired/78850f87-56e1-4d63-9618-7b549eee254f_0.png", "Description/paired/78850f87-56e1-4d63-9618-7b549eee254f_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains severe cloud artifacts that obscure a significant portion of the image, creating a hazy and unclear visual effect. Therefore, Image 1 has higher overall quality due to the absence of distortions and clearer visibility.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "c7d3e257-0c55-437d-87ba-0d23f54701d1", "images": ["Perception/single/c7d3e257-0c55-437d-87ba-0d23f54701d1_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "8f2ca35c-3fd6-4e5d-a3f6-7f2480475fb1", "images": ["Perception/paired/8f2ca35c-3fd6-4e5d-a3f6-7f2480475fb1_0.png", "Perception/paired/8f2ca35c-3fd6-4e5d-a3f6-7f2480475fb1_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.haze\nB.missing tiles\nC.cloud\nD.noise", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "91ec40c6-7a0b-47c0-85eb-0b906deca37c", "images": ["Perception/single/91ec40c6-7a0b-47c0-85eb-0b906deca37c_0.png"], "question": "What form of distortion is most apparent here?\nA.image compression\nB.dead pixel\nC.No distortion\nD.noise", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "57456d16-4b6b-4d1b-8edc-4906d5382f1a", "images": ["Perception/single/57456d16-4b6b-4d1b-8edc-4906d5382f1a_0.png"], "question": "Does haze obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "fdd537db-cb97-44f7-9b1b-f9fd332011c4", "images": ["Perception/paired/fdd537db-cb97-44f7-9b1b-f9fd332011c4_0.png", "Perception/paired/fdd537db-cb97-44f7-9b1b-f9fd332011c4_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "96ff9f1b-ffd2-41f1-bfbd-3b9c43b1625a", "images": ["Perception/single/96ff9f1b-ffd2-41f1-bfbd-3b9c43b1625a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "d6b35757-4840-4252-ad5c-bb9574c80360", "images": ["Perception/single/d6b35757-4840-4252-ad5c-bb9574c80360_0.png"], "question": "What category of distortion does this image belong to?\nA.dead pixel\nB.noise\nC.haze\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "88a6930b-e190-4873-8144-b009f2cb771b", "images": ["Perception/single/88a6930b-e190-4873-8144-b009f2cb771b_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.ghosting\nC.sidelobe\nD.striping", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "72904aa2-0b0a-4c73-bb45-f930149663ed", "images": ["Description/single/72904aa2-0b0a-4c73-bb45-f930149663ed_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The color distortion introduces a bluish tint that alters the natural appearance of vegetation and water, making the scene appear less vibrant and realistic.  \nThe altered color balance reduces the clarity of vegetation patterns and water boundaries, complicating the identification of ecological features.  \nThe image quality is moderately degraded, impacting its suitability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "7fb71d67-1ba4-4464-be8f-394ec60dcfb1", "images": ["Perception/single/7fb71d67-1ba4-4464-be8f-394ec60dcfb1_0.png"], "question": "Which distortion most significantly affects this image?\nA.missing tiles\nB.color distortion\nC.image stretching\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "76bb29bb-abd2-40e0-9140-c784f9d8608c", "images": ["Perception/single/76bb29bb-abd2-40e0-9140-c784f9d8608c_0.png"], "question": "Does dead pixel lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "6deaa328-2bcc-4480-a1eb-f7948d2e45f4", "images": ["Perception/paired/6deaa328-2bcc-4480-a1eb-f7948d2e45f4_0.png", "Perception/paired/6deaa328-2bcc-4480-a1eb-f7948d2e45f4_1.png"], "question": "Between the two images, does Image 2 display obvious distortion compared to Image 1?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6a360cee-9ce6-4dbe-9a6e-33d7129752a5", "images": ["Perception/single/6a360cee-9ce6-4dbe-9a6e-33d7129752a5_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.cloud\nB.haze\nC.image stretching\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "4d26af30-6ac0-4a63-80b8-054cbde4ed3e", "images": ["Perception/paired/4d26af30-6ac0-4a63-80b8-054cbde4ed3e_0.png", "Perception/paired/4d26af30-6ac0-4a63-80b8-054cbde4ed3e_1.png"], "question": "Which distortion label best fits the difference between these paired images?\nA.color distortion\nB.image stretching\nC.No distortion\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "845064d3-ce7c-4c80-8547-ca3cb20a01a4", "images": ["Perception/paired/845064d3-ce7c-4c80-8547-ca3cb20a01a4_0.png", "Perception/paired/845064d3-ce7c-4c80-8547-ca3cb20a01a4_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9282ebdc-7ae6-4c72-bcda-92883774d88a", "images": ["Perception/single/9282ebdc-7ae6-4c72-bcda-92883774d88a_0.png"], "question": "Does the image exhibit impulse noise?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "44d6e66e-828f-42a4-86a7-fd7853cde397", "images": ["Perception/single/44d6e66e-828f-42a4-86a7-fd7853cde397_0.png"], "question": "Does motion blur interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "2d728b89-8448-4ee3-8e12-43c3227a5b0c", "images": ["Perception/paired/2d728b89-8448-4ee3-8e12-43c3227a5b0c_0.png", "Perception/paired/2d728b89-8448-4ee3-8e12-43c3227a5b0c_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "52eff1ed-e66f-4c4e-a16f-f782b2b30e35", "images": ["Perception/single/52eff1ed-e66f-4c4e-a16f-f782b2b30e35_0.png"], "question": "Can motion blur and stripe noise be observed at the same time in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "a9241999-6a1d-4aac-8da1-ed38b657025b", "images": ["Description/paired/a9241999-6a1d-4aac-8da1-ed38b657025b_0.png", "Description/paired/a9241999-6a1d-4aac-8da1-ed38b657025b_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 exhibits moderate image stretching artifacts, which manifest as elongated and distorted features, particularly noticeable in the linear elements and overall geometry. Therefore, Image 1 has higher overall quality due to the absence of any visible distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "191defdb-72e3-453a-902f-2df6dcf0ec31", "images": ["Perception/paired/191defdb-72e3-453a-902f-2df6dcf0ec31_0.png", "Perception/paired/191defdb-72e3-453a-902f-2df6dcf0ec31_1.png"], "question": "Comparing to Image 1, does Image 2 contain image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "eafe7c1a-e521-4c57-b179-349ce8753f70", "images": ["Perception/single/eafe7c1a-e521-4c57-b179-349ce8753f70_0.png"], "question": "Does this image contain sidelobe interference?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "49715cbb-66e1-4276-95cd-8147de6fef78", "images": ["Perception/single/49715cbb-66e1-4276-95cd-8147de6fef78_0.png"], "question": "Does dead pixel compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "ef9ea652-25b9-49fe-9cb1-c530783eb4ab", "images": ["Description/single/ef9ea652-25b9-49fe-9cb1-c530783eb4ab_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe cloud distortion obscures large portions of the urban area, creating bright, undefined patches that disrupt the visibility of buildings and streets. Key features such as road networks, sports fields, and residential structures are heavily obscured, making spatial interpretation and detailed analysis nearly impossible. The image quality is poor due to the significant loss of clarity and detail caused by the cloud coverage.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "25acc8a9-2656-43d8-a72a-1e794a91dc97", "images": ["Perception/single/25acc8a9-2656-43d8-a72a-1e794a91dc97_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.color distortion\nB.image stretching\nC.No distortion\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "89fae175-4a17-4874-a808-d42f28ad1ada", "images": ["Perception/single/89fae175-4a17-4874-a808-d42f28ad1ada_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.missing tiles\nB.No distortion\nC.haze\nD.cloud", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "86f08628-bec0-442f-bf6f-3af42bd02327", "images": ["Perception/single/86f08628-bec0-442f-bf6f-3af42bd02327_0.png"], "question": "Is stripe noise responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "113f69e7-7c9c-4eb2-8722-0414a5e70a5d", "images": ["Perception/single/113f69e7-7c9c-4eb2-8722-0414a5e70a5d_0.png"], "question": "Does image compression affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "023d36ef-e463-428c-a547-d541cd1c553a", "images": ["Perception/paired/023d36ef-e463-428c-a547-d541cd1c553a_0.png", "Perception/paired/023d36ef-e463-428c-a547-d541cd1c553a_1.png"], "question": "Is color distortion present and significant in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "76a107b7-35f2-4308-afbb-9914d330b089", "images": ["Perception/single/76a107b7-35f2-4308-afbb-9914d330b089_0.png"], "question": "Is gaussian blur visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "23c0d772-5935-4673-be27-392fae6bcd7a", "images": ["Perception/single/23c0d772-5935-4673-be27-392fae6bcd7a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "854d45a3-d58e-44e4-a7fc-daa9a37da988", "images": ["Perception/paired/854d45a3-d58e-44e4-a7fc-daa9a37da988_0.png", "Perception/paired/854d45a3-d58e-44e4-a7fc-daa9a37da988_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "6af1128a-c9d7-45c6-84c5-d21e74353619", "images": ["Perception/single/6af1128a-c9d7-45c6-84c5-d21e74353619_0.png"], "question": "Does speckle noise interfere with image interpretation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "06400b05-4014-47af-85ff-5b265374c302", "images": ["Perception/single/06400b05-4014-47af-85ff-5b265374c302_0.png"], "question": "What category of distortion does this image belong to?\nA.missing tiles\nB.noise\nC.dead pixel\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "b5b1703d-b2f6-4696-8cf1-ad8e95eb1f13", "images": ["Perception/single/b5b1703d-b2f6-4696-8cf1-ad8e95eb1f13_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "0dba572a-f725-4392-b3ff-fce0ef70face", "images": ["Perception/single/0dba572a-f725-4392-b3ff-fce0ef70face_0.png"], "question": "Does missing tiles lead to information loss?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "defd1108-6e0f-4f29-a495-72e4f881b1f5", "images": ["Perception/single/defd1108-6e0f-4f29-a495-72e4f881b1f5_0.png"], "question": "Is the image impacted by the combination of missing tiles and image stretching?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "bb9294f5-7e81-427d-b0d0-cfe3fee58f1c", "images": ["Perception/single/bb9294f5-7e81-427d-b0d0-cfe3fee58f1c_0.png"], "question": "Which distortion most significantly affects this image?\nA.noise\nB.image compression\nC.haze\nD.color distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "2e6d48c2-7647-4d17-84d8-e23ddecfe6c3", "images": ["Description/paired/2e6d48c2-7647-4d17-84d8-e23ddecfe6c3_0.png", "Description/paired/2e6d48c2-7647-4d17-84d8-e23ddecfe6c3_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe compression artifacts, including blockiness, blurring, and loss of fine details, which significantly degrade the visual quality. Image 2 shows no observable distortions and retains clear details and natural texture. Image 2 has higher overall quality due to its lack of distortions and superior preservation of detail compared to the heavily degraded Image 1.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "c91ea175-ea1e-4b1e-b426-06712af8551b", "images": ["Description/paired/c91ea175-ea1e-4b1e-b426-06712af8551b_0.png", "Description/paired/c91ea175-ea1e-4b1e-b426-06712af8551b_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong haze artifacts, making the image appear washed out and reducing the visibility of details. Image 2 has no observable distortions and maintains clear and distinct details. Therefore, Image 2 has higher overall quality due to its clarity and lack of haze artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "25d968e0-458f-4dc3-800e-c884de491871", "images": ["Perception/paired/25d968e0-458f-4dc3-800e-c884de491871_0.png", "Perception/paired/25d968e0-458f-4dc3-800e-c884de491871_1.png"], "question": "Which type of corruption is evident when comparing Image 2 against Image 1?\nA.No distortion\nB.image stretching\nC.haze\nD.image compression", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e49abfd1-c3ff-40ab-8820-62bd1fa0daaa", "images": ["Perception/paired/e49abfd1-c3ff-40ab-8820-62bd1fa0daaa_0.png", "Perception/paired/e49abfd1-c3ff-40ab-8820-62bd1fa0daaa_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.image compression\nB.dead pixel\nC.image stretching\nD.color distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "938c887a-2d93-4345-a428-9c86c593b8ac", "images": ["Perception/single/938c887a-2d93-4345-a428-9c86c593b8ac_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "b405cb4e-b001-4043-a9b9-b2890a68853c", "images": ["Perception/single/b405cb4e-b001-4043-a9b9-b2890a68853c_0.png"], "question": "Does this image contain image compression and gaussian blur simultaneously?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "8e524af5-d63d-424c-8f23-4d78a452fa9b", "images": ["Perception/single/8e524af5-d63d-424c-8f23-4d78a452fa9b_0.png"], "question": "Is image compression responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "fee81e30-4b23-4402-9335-c2e858ea0dd1", "images": ["Description/single/fee81e30-4b23-4402-9335-c2e858ea0dd1_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe deadline noise introduces horizontal lines across the image, disrupting the visual continuity and making features like roads and buildings appear fragmented. The distortion obscures fine details, such as vegetation patterns and infrastructure layouts, reducing the interpretability of land use and structural elements. The image quality is poor, significantly impairing its utility for analysis or decision-making.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "c4e18bd7-b8ae-46a3-829d-679bd7864811", "images": ["Perception/paired/c4e18bd7-b8ae-46a3-829d-679bd7864811_0.png", "Perception/paired/c4e18bd7-b8ae-46a3-829d-679bd7864811_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ff9321df-dda7-4f85-b2db-5ff67430c4c6", "images": ["Perception/paired/ff9321df-dda7-4f85-b2db-5ff67430c4c6_0.png", "Perception/paired/ff9321df-dda7-4f85-b2db-5ff67430c4c6_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.missing tiles\nB.image compression\nC.No distortion\nD.cloud", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "67f0c9d7-bf0d-4d88-bf9e-e1393c7657de", "images": ["Perception/single/67f0c9d7-bf0d-4d88-bf9e-e1393c7657de_0.png"], "question": "Is dead pixel visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "8abaab4b-3d0c-4bd1-b17c-cc9a90597459", "images": ["Description/paired/8abaab4b-3d0c-4bd1-b17c-cc9a90597459_0.png", "Description/paired/8abaab4b-3d0c-4bd1-b17c-cc9a90597459_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong image stretching artifacts, visible as elongated and distorted features that disrupt the natural appearance of the terrain. Image 2 has no observable distortions and maintains a clear and undistorted representation of the landscape. Therefore, Image 2 has higher overall quality due to its lack of distortions and more accurate depiction of the terrain.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "32e1e795-b2f6-43ad-9dad-350cb77b122d", "images": ["Perception/single/32e1e795-b2f6-43ad-9dad-350cb77b122d_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "90d82c75-14b0-4440-8ee7-dae96a70267b", "images": ["Perception/single/90d82c75-14b0-4440-8ee7-dae96a70267b_0.png"], "question": "Identify the main type of corruption in this image.\nA.cloud\nB.color distortion\nC.No distortion\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "bd48dc31-7953-43f1-9b50-5bb6f1ae4db6", "images": ["Perception/paired/bd48dc31-7953-43f1-9b50-5bb6f1ae4db6_0.png", "Perception/paired/bd48dc31-7953-43f1-9b50-5bb6f1ae4db6_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.cloud\nB.No distortion\nC.image stretching\nD.image compression", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "defea8e4-4d4c-441b-8660-9b1a17276f51", "images": ["Perception/single/defea8e4-4d4c-441b-8660-9b1a17276f51_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "ebd26a7b-3d44-451d-9311-21d07fa7e490", "images": ["Perception/single/ebd26a7b-3d44-451d-9311-21d07fa7e490_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "25e58f21-805b-4eb3-9657-737d9d213d28", "images": ["Perception/single/25e58f21-805b-4eb3-9657-737d9d213d28_0.png"], "question": "Does image compression affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "edc638bf-2fd3-414b-b957-66821e3911d6", "images": ["Perception/paired/edc638bf-2fd3-414b-b957-66821e3911d6_0.png", "Perception/paired/edc638bf-2fd3-414b-b957-66821e3911d6_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable cloud artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "58d4738a-7e19-45aa-9f5f-3f58858432b6", "images": ["Perception/paired/58d4738a-7e19-45aa-9f5f-3f58858432b6_0.png", "Perception/paired/58d4738a-7e19-45aa-9f5f-3f58858432b6_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "43804572-48f1-427e-af04-21198d3b56b8", "images": ["Perception/single/43804572-48f1-427e-af04-21198d3b56b8_0.png"], "question": "Is sidelobe interference the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "ff68f514-bc07-4107-86b2-0ba79fc687b2", "images": ["Perception/paired/ff68f514-bc07-4107-86b2-0ba79fc687b2_0.png", "Perception/paired/ff68f514-bc07-4107-86b2-0ba79fc687b2_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.No distortion\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d6dd4cef-b274-4d56-abaf-39bf30b2000c", "images": ["Perception/single/d6dd4cef-b274-4d56-abaf-39bf30b2000c_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.noise\nB.haze\nC.image compression\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "72e498a5-09f7-4c0f-af3a-9ab501954dde", "images": ["Perception/single/72e498a5-09f7-4c0f-af3a-9ab501954dde_0.png"], "question": "Can impulse noise be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "a71d53cf-be61-4891-81ed-2199295e7d1d", "images": ["Perception/single/a71d53cf-be61-4891-81ed-2199295e7d1d_0.png"], "question": "Is the image impacted by gaussian noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "23feece4-264b-4475-b667-401d24f710a3", "images": ["Perception/single/23feece4-264b-4475-b667-401d24f710a3_0.png"], "question": "What category of distortion does this image belong to?\nA.image stretching\nB.dead pixel\nC.No distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "15768698-2cea-4413-a75e-5b7080ab883d", "images": ["Perception/single/15768698-2cea-4413-a75e-5b7080ab883d_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.color distortion\nB.image compression\nC.blur\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "4e6737c8-be4c-457f-bc28-98c60451b45a", "images": ["Perception/single/4e6737c8-be4c-457f-bc28-98c60451b45a_0.png"], "question": "Does image compression result in missing information?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "32076981-e518-4a3b-b6c0-de58550d9f77", "images": ["Perception/single/32076981-e518-4a3b-b6c0-de58550d9f77_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "e0364d81-4487-4517-ba58-13011c850f03", "images": ["Perception/single/e0364d81-4487-4517-ba58-13011c850f03_0.png"], "question": "Does impulse noise lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "afad3263-74a4-4095-bb7a-0029dd7ac4e3", "images": ["Perception/paired/afad3263-74a4-4095-bb7a-0029dd7ac4e3_0.png", "Perception/paired/afad3263-74a4-4095-bb7a-0029dd7ac4e3_1.png"], "question": "What artifact has been applied to Image 2 when compared to Image 1?\nA.cloud\nB.dead pixel\nC.No distortion\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "59c6d430-7c30-4736-b7fd-b3dd25abcc6e", "images": ["Perception/paired/59c6d430-7c30-4736-b7fd-b3dd25abcc6e_0.png", "Perception/paired/59c6d430-7c30-4736-b7fd-b3dd25abcc6e_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of cloud?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "65d34bc9-2fa5-4682-bdcf-a782d39b83d4", "images": ["Description/single/65d34bc9-2fa5-4682-bdcf-a782d39b83d4_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces noticeable blocky artifacts and blurring, disrupting the smooth transitions in vegetation and water surfaces. The distortion obscures fine details, such as individual building edges and vegetation textures, making it difficult to distinguish features accurately. The image quality is poor, significantly limiting its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "44801d60-37c6-4d7d-a371-015e4d11420f", "images": ["Perception/single/44801d60-37c6-4d7d-a371-015e4d11420f_0.png"], "question": "Is color distortion the main factor in this distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "2e8f0059-00aa-4778-8e9f-dae68cdfe569", "images": ["Perception/single/2e8f0059-00aa-4778-8e9f-dae68cdfe569_0.png"], "question": "Is sidelobe interference the main factor in this distortion?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "e1ca68f4-ea0a-477a-8177-89278819a9e0", "images": ["Perception/single/e1ca68f4-ea0a-477a-8177-89278819a9e0_0.png"], "question": "Is haze visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "3d625b84-b052-4361-a42b-72fd986b11a4", "images": ["Perception/single/3d625b84-b052-4361-a42b-72fd986b11a4_0.png"], "question": "Does this image contain image compression and stripe noise simultaneously?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "234e0dfb-e073-496c-b6ec-f79a208d0400", "images": ["Perception/single/234e0dfb-e073-496c-b6ec-f79a208d0400_0.png"], "question": "Is image compression the main factor in this distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "aacefb1e-83ce-4185-9617-cb1436ce5c70", "images": ["Perception/paired/aacefb1e-83ce-4185-9617-cb1436ce5c70_0.png", "Perception/paired/aacefb1e-83ce-4185-9617-cb1436ce5c70_1.png"], "question": "Identify the main distortion introduced between the two images.\nA.image compression\nB.noise\nC.color distortion\nD.dead pixel", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "36e06266-b4ca-47a2-a28f-54503511f2c4", "images": ["Perception/paired/36e06266-b4ca-47a2-a28f-54503511f2c4_0.png", "Perception/paired/36e06266-b4ca-47a2-a28f-54503511f2c4_1.png"], "question": "Comparing Image 1 (reference) and Image 2 (degraded), what distortion best explains the difference?\nA.haze\nB.color distortion\nC.image stretching\nD.No distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "744d98a5-a371-44ab-9942-4061210660f2", "images": ["Perception/single/744d98a5-a371-44ab-9942-4061210660f2_0.png"], "question": "Does dead pixel compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "7faab426-8065-4697-b0b3-74bda9850433", "images": ["Perception/single/7faab426-8065-4697-b0b3-74bda9850433_0.png"], "question": "Is the image impacted by missing tiles?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "971ce004-32fb-4e74-989e-3dc9fd9ca1db", "images": ["Perception/single/971ce004-32fb-4e74-989e-3dc9fd9ca1db_0.png"], "question": "Which distortion most significantly affects this image?\nA.image stretching\nB.haze\nC.noise\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "f44bfa52-4deb-4899-8851-f7c603cb7d4e", "images": ["Perception/paired/f44bfa52-4deb-4899-8851-f7c603cb7d4e_0.png", "Perception/paired/f44bfa52-4deb-4899-8851-f7c603cb7d4e_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.noise\nB.cloud\nC.image compression\nD.blur", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "62a173cd-bfab-41ad-806f-dcfd4c1efef1", "images": ["Perception/single/62a173cd-bfab-41ad-806f-dcfd4c1efef1_0.png"], "question": "What form of distortion is most apparent here?\nA.No distortion\nB.image stretching\nC.dead pixel\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "9de782fc-67bb-4060-bb48-3959e7d2741e", "images": ["Perception/paired/9de782fc-67bb-4060-bb48-3959e7d2741e_0.png", "Perception/paired/9de782fc-67bb-4060-bb48-3959e7d2741e_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.haze\nB.blur\nC.image compression\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "3ac87b49-6744-4c62-a783-44367bb454b9", "images": ["Perception/paired/3ac87b49-6744-4c62-a783-44367bb454b9_0.png", "Perception/paired/3ac87b49-6744-4c62-a783-44367bb454b9_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.No distortion\nB.blur\nC.image compression\nD.haze", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "60ef679e-b7db-4f06-9316-51c03f62f0da", "images": ["Perception/single/60ef679e-b7db-4f06-9316-51c03f62f0da_0.png"], "question": "Is image compression a dominant distortion in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "bcfa0f01-e47d-4b2c-8631-53033ec3ffb5", "images": ["Perception/single/bcfa0f01-e47d-4b2c-8631-53033ec3ffb5_0.png"], "question": "What visual defect does this image exhibit?\nA.No distortion\nB.color distortion\nC.cloud\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "afa26086-aef9-4428-9a81-5657e73c521d", "images": ["Perception/paired/afa26086-aef9-4428-9a81-5657e73c521d_0.png", "Perception/paired/afa26086-aef9-4428-9a81-5657e73c521d_1.png"], "question": "What artifact has been applied to Image 2 when compared to Image 1?\nA.blur\nB.dead pixel\nC.missing tiles\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "b4dbd297-974c-4105-b9e7-bce682d5afbf", "images": ["Perception/single/b4dbd297-974c-4105-b9e7-bce682d5afbf_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "9401f5d4-ab08-4daa-b624-9db14916bcda", "images": ["Perception/single/9401f5d4-ab08-4daa-b624-9db14916bcda_0.png"], "question": "Is image compression a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "c6bdc5c3-15d6-4847-8f47-f19032c5e8d8", "images": ["Perception/single/c6bdc5c3-15d6-4847-8f47-f19032c5e8d8_0.png"], "question": "Does dead pixel obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "ae4c7785-6a63-4af6-b5d0-8a9ce5a8c319", "images": ["Perception/paired/ae4c7785-6a63-4af6-b5d0-8a9ce5a8c319_0.png", "Perception/paired/ae4c7785-6a63-4af6-b5d0-8a9ce5a8c319_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of missing tiles?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a7403763-e0e6-4454-bbb0-3f981e0ac998", "images": ["Perception/single/a7403763-e0e6-4454-bbb0-3f981e0ac998_0.png"], "question": "Does image compression compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "64eb00ab-38df-4755-82d1-5468ff864abf", "images": ["Description/paired/64eb00ab-38df-4755-82d1-5468ff864abf_0.png", "Description/paired/64eb00ab-38df-4755-82d1-5468ff864abf_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe color distortion, with a noticeable greenish tint and reduced color fidelity, making the details less clear and the colors appear unnatural. Image 2 has no observable distortions, maintaining accurate color representation and clearer details. Therefore, Image 2 has higher overall quality due to its accurate color representation and clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "c17e6647-1beb-4298-b8eb-c1f3eb39bff1", "images": ["Perception/single/c17e6647-1beb-4298-b8eb-c1f3eb39bff1_0.png"], "question": "Is image stretching the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "1d4eb1c6-ea04-44b1-99a9-d8c817745a6c", "images": ["Perception/paired/1d4eb1c6-ea04-44b1-99a9-d8c817745a6c_0.png", "Perception/paired/1d4eb1c6-ea04-44b1-99a9-d8c817745a6c_1.png"], "question": "Compare Image 2 to Image 1 and choose the severity of distortion.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "6272a300-2a74-4062-aa5c-025d93cd1faa", "images": ["Perception/single/6272a300-2a74-4062-aa5c-025d93cd1faa_0.png"], "question": "Is stripe noise the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "640c3b97-6964-409a-989f-09ab7684ef69", "images": ["Perception/single/640c3b97-6964-409a-989f-09ab7684ef69_0.png"], "question": "Is motion blur responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "3f9f5ce9-de93-4f66-896b-33a64f54d761", "images": ["Description/single/3f9f5ce9-de93-4f66-896b-33a64f54d761_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Dense cloud coverage obscures large portions of the farmland, creating bright patches and reducing visibility of field boundaries.  \nThe severe cloud distortion eliminates critical details, such as the texture and structure of agricultural plots, making land use analysis difficult.  \nThe image quality is poor due to significant visual obstructions and loss of spatial information.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "2f978497-ef61-40f1-b74d-b629e75c89de", "images": ["Perception/single/2f978497-ef61-40f1-b74d-b629e75c89de_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "fb9e6f00-4306-4fcc-b5fb-2d74a54cda4d", "images": ["Perception/paired/fb9e6f00-4306-4fcc-b5fb-2d74a54cda4d_0.png", "Perception/paired/fb9e6f00-4306-4fcc-b5fb-2d74a54cda4d_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "25a29363-4371-4e85-831e-189311e1bd39", "images": ["Perception/single/25a29363-4371-4e85-831e-189311e1bd39_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "008fbd5f-2993-425b-9ab2-07f3a7416929", "images": ["Perception/single/008fbd5f-2993-425b-9ab2-07f3a7416929_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "8f89123b-ea62-4c0e-889f-3f60d8ae4b59", "images": ["Perception/paired/8f89123b-ea62-4c0e-889f-3f60d8ae4b59_0.png", "Perception/paired/8f89123b-ea62-4c0e-889f-3f60d8ae4b59_1.png"], "question": "Is dead pixel responsible for visual artifacts in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "73551621-f21a-489c-88c8-cdb56f644a39", "images": ["Perception/single/73551621-f21a-489c-88c8-cdb56f644a39_0.png"], "question": "What category of distortion does this image belong to?\nA.image stretching\nB.dead pixel\nC.No distortion\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "c5867f7b-e488-4401-b1bc-79d962c41dc1", "images": ["Perception/paired/c5867f7b-e488-4401-b1bc-79d962c41dc1_0.png", "Perception/paired/c5867f7b-e488-4401-b1bc-79d962c41dc1_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ae3d0c81-c702-4d07-aaa0-6f7eb6c5b720", "images": ["Perception/paired/ae3d0c81-c702-4d07-aaa0-6f7eb6c5b720_0.png", "Perception/paired/ae3d0c81-c702-4d07-aaa0-6f7eb6c5b720_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e73c209d-cc74-46a4-b90b-32cfe43dea12", "images": ["Perception/single/e73c209d-cc74-46a4-b90b-32cfe43dea12_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.image stretching\nB.missing tiles\nC.noise\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "5a1ae16b-1ff2-435e-b42d-3ecc8d2c975e", "images": ["Perception/paired/5a1ae16b-1ff2-435e-b42d-3ecc8d2c975e_0.png", "Perception/paired/5a1ae16b-1ff2-435e-b42d-3ecc8d2c975e_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ecb2421f-8a11-4944-bc7c-62e7dc46aa3c", "images": ["Perception/paired/ecb2421f-8a11-4944-bc7c-62e7dc46aa3c_0.png", "Perception/paired/ecb2421f-8a11-4944-bc7c-62e7dc46aa3c_1.png"], "question": "What artifact has been applied to Image 2 when compared to Image 1?\nA.cloud\nB.dead pixel\nC.image compression\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cb4fecee-0d89-43c7-9877-6fbfcd187846", "images": ["Perception/single/cb4fecee-0d89-43c7-9877-6fbfcd187846_0.png"], "question": "What type of distortion is visible here?\nA.noise\nB.No distortion\nC.blur\nD.image stretching", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "2d0313a5-554f-47ed-8d49-f8b0e4214694", "images": ["Perception/single/2d0313a5-554f-47ed-8d49-f8b0e4214694_0.png"], "question": "Is the image impacted by sidelobe interference?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "93db3b3f-ec41-4ced-b1b1-690e745708d4", "images": ["Description/paired/93db3b3f-ec41-4ced-b1b1-690e745708d4_0.png", "Description/paired/93db3b3f-ec41-4ced-b1b1-690e745708d4_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clear and sharp. Image 2 contains severe haze artifacts, making the image appear washed out and significantly reducing visibility and contrast. Therefore, Image 1 has higher overall quality due to its clarity and lack of distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "0614f775-aaca-4f84-9dbc-34d49aab4ec7", "images": ["Perception/single/0614f775-aaca-4f84-9dbc-34d49aab4ec7_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.speckle\nC.ghosting\nD.striping", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "b9a73d96-1f25-40f6-89b0-1a4f76f913cf", "images": ["Description/paired/b9a73d96-1f25-40f6-89b0-1a4f76f913cf_0.png", "Description/paired/b9a73d96-1f25-40f6-89b0-1a4f76f913cf_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains strong haze artifacts, which manifest as a whitish, translucent layer that reduces the overall contrast and clarity of the image. Therefore, Image 1 has higher overall quality due to the absence of distortions and the presence of clear, sharp details.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "73f5028d-90de-4fa8-938d-9b1f7c0d4306", "images": ["Perception/paired/73f5028d-90de-4fa8-938d-9b1f7c0d4306_0.png", "Perception/paired/73f5028d-90de-4fa8-938d-9b1f7c0d4306_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "881c77bb-0434-412f-8bc9-ca333a25a6ba", "images": ["Perception/single/881c77bb-0434-412f-8bc9-ca333a25a6ba_0.png"], "question": "Does cloud lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "72dee0a9-ada2-4b8d-b4c4-285d911b2732", "images": ["Description/paired/72dee0a9-ada2-4b8d-b4c4-285d911b2732_0.png", "Description/paired/72dee0a9-ada2-4b8d-b4c4-285d911b2732_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and natural. Image 2 contains strong color distortion artifacts, with a pervasive pinkish-red hue that affects the entire image, making it look unnatural. Therefore, Image 1 has higher overall quality due to its lack of distortions and more natural appearance.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "95335a35-8f47-4554-9472-289c1395c7fd", "images": ["Perception/single/95335a35-8f47-4554-9472-289c1395c7fd_0.png"], "question": "Select all types of distortions affecting this image.\nA. motion blur\nB. haze\nC. dead pixel\nD. impulse noise", "answer": "A,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "a7348b4b-b9a4-4481-a995-6d176d72ab0a", "images": ["Perception/paired/a7348b4b-b9a4-4481-a995-6d176d72ab0a_0.png", "Perception/paired/a7348b4b-b9a4-4481-a995-6d176d72ab0a_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3d36e683-747e-45d7-bf39-3a8377c5b9c5", "images": ["Perception/single/3d36e683-747e-45d7-bf39-3a8377c5b9c5_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "9169272b-dfc5-49cd-b6d6-4ed045a7ea83", "images": ["Perception/single/9169272b-dfc5-49cd-b6d6-4ed045a7ea83_0.png"], "question": "Is spatially correlated noise present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "7c3159fb-d5ef-4614-abd8-340e39791f45", "images": ["Perception/single/7c3159fb-d5ef-4614-abd8-340e39791f45_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "0f88276b-9afa-4b9f-af61-d1cb1d64a369", "images": ["Perception/single/0f88276b-9afa-4b9f-af61-d1cb1d64a369_0.png"], "question": "Is dead pixel the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "bba56522-e531-42ab-8b2b-cd52e7927153", "images": ["Perception/paired/bba56522-e531-42ab-8b2b-cd52e7927153_0.png", "Perception/paired/bba56522-e531-42ab-8b2b-cd52e7927153_1.png"], "question": "Is image compression apparent in this remote sensing scene (Image 2)?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "a6fc4410-8aaf-4ca9-8337-72e585d69a31", "images": ["Description/single/a6fc4410-8aaf-4ca9-8337-72e585d69a31_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe spatially correlated noise creates a grainy texture that disrupts the uniform appearance of the landscape and introduces unnatural patterns across the image. The noise obscures fine details, such as vegetation distribution and field boundaries, making it difficult to interpret land use or identify specific features. The image quality is poor, significantly limiting its usability for analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "e910592c-f80e-4bc7-a22d-c35a343090c8", "images": ["Perception/single/e910592c-f80e-4bc7-a22d-c35a343090c8_0.png"], "question": "What is the primary distortion type in this image?\nA.cloud\nB.haze\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "badc1598-7603-4888-8e6f-900b7768d89a", "images": ["Perception/single/badc1598-7603-4888-8e6f-900b7768d89a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "844f1d4a-45fa-4d2d-8b44-0f7695bf4564", "images": ["Perception/paired/844f1d4a-45fa-4d2d-8b44-0f7695bf4564_0.png", "Perception/paired/844f1d4a-45fa-4d2d-8b44-0f7695bf4564_1.png"], "question": "Is gaussian noise a dominant distortion in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "d458fcd1-0710-4c0a-8141-0456bc2c470a", "images": ["Perception/paired/d458fcd1-0710-4c0a-8141-0456bc2c470a_0.png", "Perception/paired/d458fcd1-0710-4c0a-8141-0456bc2c470a_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.image compression\nB.No distortion\nC.color distortion\nD.missing tiles", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "3561638b-d595-4b90-bdf0-2b83da7bf332", "images": ["Perception/single/3561638b-d595-4b90-bdf0-2b83da7bf332_0.png"], "question": "Are gaussian blur and haze present together in the scene?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "4dc21f06-988f-49a2-a16e-6bbe4b18d9a3", "images": ["Perception/single/4dc21f06-988f-49a2-a16e-6bbe4b18d9a3_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "0e54fc16-7268-49d0-98c5-8e9047909ea5", "images": ["Perception/single/0e54fc16-7268-49d0-98c5-8e9047909ea5_0.png"], "question": "Is there sidelobe interference present in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "9f78afbf-b9f7-4025-8645-858a63387ca7", "images": ["Perception/single/9f78afbf-b9f7-4025-8645-858a63387ca7_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.noise\nB.missing tiles\nC.image compression\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "f922a0a5-01c7-4b69-9289-c79c9123e3ec", "images": ["Perception/single/f922a0a5-01c7-4b69-9289-c79c9123e3ec_0.png"], "question": "Does the image exhibit haze?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f003145c-fc18-4638-b99d-8175783caad3", "images": ["Perception/single/f003145c-fc18-4638-b99d-8175783caad3_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.image stretching\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "7ece4338-11d9-4515-95d2-a75c7f005640", "images": ["Perception/single/7ece4338-11d9-4515-95d2-a75c7f005640_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "ca8ef4e1-e2a1-4653-aa7a-fb915fb05e5a", "images": ["Perception/single/ca8ef4e1-e2a1-4653-aa7a-fb915fb05e5a_0.png"], "question": "What visual defect does this image exhibit?\nA.missing tiles\nB.No distortion\nC.blur\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "218667f2-7096-45de-ab43-15419e3dfff2", "images": ["Description/single/218667f2-7096-45de-ab43-15419e3dfff2_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The color distortion introduces a muted and unnatural tone, making the landscape appear less vibrant and realistic. Variations in vegetation and terrain are harder to distinguish, reducing the clarity of spatial patterns and surface features. The image quality is moderately degraded, impacting its usability for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "4286d0c6-b664-4737-bc09-d9e993bdacde", "images": ["Perception/paired/4286d0c6-b664-4737-bc09-d9e993bdacde_0.png", "Perception/paired/4286d0c6-b664-4737-bc09-d9e993bdacde_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of haze?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7222ae8e-92d6-41d5-a678-9984aed2eaa5", "images": ["Perception/single/7222ae8e-92d6-41d5-a678-9984aed2eaa5_0.png"], "question": "Which distortion most significantly affects this image?\nA.No distortion\nB.image stretching\nC.color distortion\nD.dead pixel", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "2d53b95b-6f1b-4e0f-b339-8e790294f867", "images": ["Perception/single/2d53b95b-6f1b-4e0f-b339-8e790294f867_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "f10099f8-8e48-4fa1-825f-e1c9b91ce43b", "images": ["Perception/single/f10099f8-8e48-4fa1-825f-e1c9b91ce43b_0.jpg"], "question": "Does gaussian noise affect the image quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "c3d138f3-f660-49ba-ad2e-c63f3a6402cd", "images": ["Description/paired/c3d138f3-f660-49ba-ad2e-c63f3a6402cd_0.png", "Description/paired/c3d138f3-f660-49ba-ad2e-c63f3a6402cd_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 contains strong missing tiles artifacts, evident as a large white square in the bottom left corner. Therefore, Image 1 has higher overall quality due to the absence of any distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "a60df0cf-10b4-4b83-9881-4195774da3bb", "images": ["Perception/single/a60df0cf-10b4-4b83-9881-4195774da3bb_0.png"], "question": "What visual defect does this image exhibit?\nA.blur\nB.color distortion\nC.cloud\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "dbaf922d-dff5-4764-9152-d32dc1a2a641", "images": ["Perception/paired/dbaf922d-dff5-4764-9152-d32dc1a2a641_0.png", "Perception/paired/dbaf922d-dff5-4764-9152-d32dc1a2a641_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.blur\nB.noise\nC.image compression\nD.image stretching", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "9cd73c61-f30d-44c9-a7e2-a1e4fe065473", "images": ["Perception/single/9cd73c61-f30d-44c9-a7e2-a1e4fe065473_0.png"], "question": "What is the dominant distortion in this image?\nA.haze\nB.dead pixel\nC.No distortion\nD.blur", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "abee9457-ef89-412b-a569-37f9491bbe2f", "images": ["Perception/paired/abee9457-ef89-412b-a569-37f9491bbe2f_0.png", "Perception/paired/abee9457-ef89-412b-a569-37f9491bbe2f_1.png"], "question": "Which distortion category describes the changes from Image 1 to Image 2?\nA.haze\nB.image stretching\nC.cloud\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d9df019e-f7fc-4675-8aea-2a427e3f1b8e", "images": ["Perception/single/d9df019e-f7fc-4675-8aea-2a427e3f1b8e_0.png"], "question": "What is the main cause of degradation in this image?\nA.dead pixel\nB.noise\nC.color distortion\nD.cloud", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "ff9232bf-68e7-415f-8fb2-7f1c22853151", "images": ["Perception/single/ff9232bf-68e7-415f-8fb2-7f1c22853151_0.png"], "question": "Does haze reduce the usability of the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "4498a53f-cff3-4c89-b782-61daf0281a79", "images": ["Perception/paired/4498a53f-cff3-4c89-b782-61daf0281a79_0.png", "Perception/paired/4498a53f-cff3-4c89-b782-61daf0281a79_1.png"], "question": "What degradation type transforms Image 1 into Image 2?\nA.missing tiles\nB.cloud\nC.image stretching\nD.blur", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9df28fba-8fbf-46e9-9625-5e695997f522", "images": ["Perception/paired/9df28fba-8fbf-46e9-9625-5e695997f522_0.png", "Perception/paired/9df28fba-8fbf-46e9-9625-5e695997f522_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "2e51126b-c9e1-435c-9c34-9628c9b204bf", "images": ["Perception/single/2e51126b-c9e1-435c-9c34-9628c9b204bf_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "3c9ee51f-070d-4aa8-ac86-4015fab6623f", "images": ["Perception/single/3c9ee51f-070d-4aa8-ac86-4015fab6623f_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.dead pixel\nB.haze\nC.color distortion\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "dec86e49-fb89-4015-91e9-713adbd07d14", "images": ["Perception/paired/dec86e49-fb89-4015-91e9-713adbd07d14_0.png", "Perception/paired/dec86e49-fb89-4015-91e9-713adbd07d14_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9bd894d0-d9ba-4a11-9b11-68088dab6156", "images": ["Perception/single/9bd894d0-d9ba-4a11-9b11-68088dab6156_0.png"], "question": "Is color distortion apparent in this remote sensing scene?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "eceb4bd7-abe8-4340-8f3c-84a2146f2d63", "images": ["Perception/single/eceb4bd7-abe8-4340-8f3c-84a2146f2d63_0.png"], "question": "What form of distortion is most apparent here?\nA.noise\nB.dead pixel\nC.haze\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "2a01d0c6-cef0-4d02-8f20-11b09eff2c71", "images": ["Perception/single/2a01d0c6-cef0-4d02-8f20-11b09eff2c71_0.png"], "question": "What category of distortion does this image belong to?\nA.missing tiles\nB.cloud\nC.haze\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "265b6e32-4b6f-494c-a5bd-54a4a880f0bf", "images": ["Perception/single/265b6e32-4b6f-494c-a5bd-54a4a880f0bf_0.png"], "question": "What category of distortion does this image belong to?\nA.image compression\nB.No distortion\nC.noise\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "b6850386-7459-488d-8efd-13ac18b25097", "images": ["Description/single/b6850386-7459-488d-8efd-13ac18b25097_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces significant blurring and pixelation, causing the terrain to appear smeared and details to be indistinct. The loss of fine texture and clarity makes it difficult to discern vegetation patterns and subtle landform features. The image quality is poor, with reduced usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "b62abc25-373a-424e-9db4-d16698b2ff21", "images": ["Perception/single/b62abc25-373a-424e-9db4-d16698b2ff21_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "9a31b59a-d412-4ce7-bd2c-de6b7d8f0d62", "images": ["Perception/paired/9a31b59a-d412-4ce7-bd2c-de6b7d8f0d62_0.png", "Perception/paired/9a31b59a-d412-4ce7-bd2c-de6b7d8f0d62_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable impulse noise artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "1f30680c-76c2-4590-8637-924bbc32e36e", "images": ["Perception/paired/1f30680c-76c2-4590-8637-924bbc32e36e_0.png", "Perception/paired/1f30680c-76c2-4590-8637-924bbc32e36e_1.png"], "question": "Looking at the two images, what artifact is primarily introduced in Image 2?\nA.missing tiles\nB.dead pixel\nC.No distortion\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cb69be7b-b086-43c6-b080-b12b8f32a864", "images": ["Perception/single/cb69be7b-b086-43c6-b080-b12b8f32a864_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "b138cc73-2a39-4bc5-82e9-c39702bf9311", "images": ["Perception/single/b138cc73-2a39-4bc5-82e9-c39702bf9311_0.jpg"], "question": "Can spatially correlated noise be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "7b3b053a-69f6-4718-a196-2bdf5a25be43", "images": ["Perception/single/7b3b053a-69f6-4718-a196-2bdf5a25be43_0.png"], "question": "What distortion is present in the image?\nA.blur\nB.missing tiles\nC.image stretching\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "aa659b65-a333-47c0-80ad-e680380ea91b", "images": ["Perception/single/aa659b65-a333-47c0-80ad-e680380ea91b_0.png"], "question": "Is sidelobe interference the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "98959f97-2f0e-45db-a2b5-e88e7c1d54e2", "images": ["Perception/paired/98959f97-2f0e-45db-a2b5-e88e7c1d54e2_0.png", "Perception/paired/98959f97-2f0e-45db-a2b5-e88e7c1d54e2_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "c43c1d9d-b990-4bbd-bf1d-e1139db7bb84", "images": ["Perception/paired/c43c1d9d-b990-4bbd-bf1d-e1139db7bb84_0.png", "Perception/paired/c43c1d9d-b990-4bbd-bf1d-e1139db7bb84_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.image compression\nB.dead pixel\nC.missing tiles\nD.noise", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "015670ba-3eb9-4c0c-80fb-c6e50acf6fdd", "images": ["Perception/single/015670ba-3eb9-4c0c-80fb-c6e50acf6fdd_0.png"], "question": "Is there stripe noise present in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "de411f77-e785-444e-82b1-ce6f6e263867", "images": ["Perception/single/de411f77-e785-444e-82b1-ce6f6e263867_0.png"], "question": "Can spatially correlated noise be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "c48a453d-6e5f-4b24-8bd5-dc52538a80ff", "images": ["Perception/paired/c48a453d-6e5f-4b24-8bd5-dc52538a80ff_0.png", "Perception/paired/c48a453d-6e5f-4b24-8bd5-dc52538a80ff_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable missing tiles artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f9a62c8e-5ddb-408d-b04c-101af4f617db", "images": ["Perception/paired/f9a62c8e-5ddb-408d-b04c-101af4f617db_0.png", "Perception/paired/f9a62c8e-5ddb-408d-b04c-101af4f617db_1.png"], "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "4ed1cec3-2cd2-4daf-8ff7-3c088f63c088", "images": ["Description/single/4ed1cec3-2cd2-4daf-8ff7-3c088f63c088_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Moderate image compression introduces slight blurring, softening the edges of buildings and reducing the sharpness of urban details. The compression diminishes interpretability by obscuring fine textures in vegetation and making road centerlines less distinct. The image quality is fair but lacks clarity for detailed analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "bbe36fff-f6f8-4169-98fc-24c1a141d1c5", "images": ["Perception/paired/bbe36fff-f6f8-4169-98fc-24c1a141d1c5_0.png", "Perception/paired/bbe36fff-f6f8-4169-98fc-24c1a141d1c5_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "4b0dfc31-a38c-4bae-864a-c90e8d26defd", "images": ["Description/paired/4b0dfc31-a38c-4bae-864a-c90e8d26defd_0.png", "Description/paired/4b0dfc31-a38c-4bae-864a-c90e8d26defd_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong motion blur artifacts, making the details appear smeared and reducing the overall sharpness and clarity. Image 2 shows no observable distortions and maintains clear and sharp details throughout the scene. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "e41667a3-c21d-4941-8de7-2031f7f124c7", "images": ["Perception/single/e41667a3-c21d-4941-8de7-2031f7f124c7_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "10447e1c-9ad4-43cf-917f-48f4c0121629", "images": ["Perception/paired/10447e1c-9ad4-43cf-917f-48f4c0121629_0.png", "Perception/paired/10447e1c-9ad4-43cf-917f-48f4c0121629_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "83ba30e3-7ce7-4720-9f89-8b94ea28d059", "images": ["Perception/single/83ba30e3-7ce7-4720-9f89-8b94ea28d059_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.ghosting\nC.sidelobe\nD.striping", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "4ffd014e-bb6c-41f9-a036-6eaca774fe65", "images": ["Perception/paired/4ffd014e-bb6c-41f9-a036-6eaca774fe65_0.png", "Perception/paired/4ffd014e-bb6c-41f9-a036-6eaca774fe65_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a5c01e43-6379-4353-9635-7fe8e268fbcf", "images": ["Perception/single/a5c01e43-6379-4353-9635-7fe8e268fbcf_0.png"], "question": "Is impulse noise a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "a1fa7b84-b7d8-43c7-9f0c-b15f230f89e1", "images": ["Perception/single/a1fa7b84-b7d8-43c7-9f0c-b15f230f89e1_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "4412804e-204c-4073-8829-f268488caeb2", "images": ["Perception/single/4412804e-204c-4073-8829-f268488caeb2_0.png"], "question": "Identify the main type of corruption in this image.\nA.blur\nB.dead pixel\nC.No distortion\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "c9e2edc2-33fb-4700-a437-d59b8f99dd72", "images": ["Perception/single/c9e2edc2-33fb-4700-a437-d59b8f99dd72_0.png"], "question": "Does deadline noise reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "235090ec-2403-48fe-ba4a-ca37dc9c7968", "images": ["Description/single/235090ec-2403-48fe-ba4a-ca37dc9c7968_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe motion blur causes a loss of sharpness, making field boundaries and vegetation textures appear smeared and indistinct.  \nThe distortion obscures critical details, such as the clarity of farmland patterns and the definition of linear features like roads or paths.  \nThe image quality is poor, significantly hindering its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "98197385-5559-4c35-bd73-f45e8067e8de", "images": ["Perception/single/98197385-5559-4c35-bd73-f45e8067e8de_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "37d54436-e651-4e16-90f4-118cb27d6e59", "images": ["Description/single/37d54436-e651-4e16-90f4-118cb27d6e59_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Large missing tiles create abrupt blank areas that disrupt the continuity of the landscape, making the image appear fragmented and incomplete.  \nThe severe gaps obscure critical details such as vegetation patterns and terrain features, significantly reducing the ability to analyze land use or environmental conditions.  \nThe image quality is poor due to the extensive loss of visual information and spatial coherence.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "21c776bb-06ca-4985-bce9-6be5264d7a63", "images": ["Perception/paired/21c776bb-06ca-4985-bce9-6be5264d7a63_0.png", "Perception/paired/21c776bb-06ca-4985-bce9-6be5264d7a63_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.blur\nB.No distortion\nC.haze\nD.color distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "35345b00-a937-4c35-93f1-e6e38976025d", "images": ["Perception/single/35345b00-a937-4c35-93f1-e6e38976025d_0.png"], "question": "What category of distortion does this image belong to?\nA.color distortion\nB.blur\nC.noise\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "b42812f7-bd2a-4a6b-916f-c0b5ed65330a", "images": ["Perception/single/b42812f7-bd2a-4a6b-916f-c0b5ed65330a_0.png"], "question": "Is motion blur the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "8d846ce2-0a36-4f41-9a46-c6414852147c", "images": ["Perception/single/8d846ce2-0a36-4f41-9a46-c6414852147c_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.cloud\nB.haze\nC.image stretching\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "967e855a-d143-4824-b0dc-552b0e2cf9e6", "images": ["Perception/paired/967e855a-d143-4824-b0dc-552b0e2cf9e6_0.png", "Perception/paired/967e855a-d143-4824-b0dc-552b0e2cf9e6_1.png"], "question": "How much quality degradation do you observe in the distorted image versus the reference?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "0aacafdc-4c24-4703-b83e-2065a494f667", "images": ["Description/single/0aacafdc-4c24-4703-b83e-2065a494f667_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe motion blur causes significant smearing of details, making building edges and vegetation boundaries appear indistinct and soft. The distortion obscures critical features such as road outlines and individual tree textures, reducing the ability to interpret spatial relationships and land cover accurately. The image quality is poor, with diminished clarity and analytical usability.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "c2762593-2eb4-49a1-9cad-c051b2ca1a03", "images": ["Perception/single/c2762593-2eb4-49a1-9cad-c051b2ca1a03_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.haze\nB.noise\nC.image stretching\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "88cd87b4-461d-4b32-8d5b-49bd25190bec", "images": ["Description/paired/88cd87b4-461d-4b32-8d5b-49bd25190bec_0.png", "Description/paired/88cd87b4-461d-4b32-8d5b-49bd25190bec_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains severe deadline noise artifacts, which appear as horizontal lines disrupting the visual continuity of the image. Image 2 has no observable distortions and appears clean and clear. Therefore, Image 2 has higher overall quality due to the absence of any visible artifacts.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "203a71cb-c928-45d5-9a51-f3211ddda2e1", "images": ["Perception/single/203a71cb-c928-45d5-9a51-f3211ddda2e1_0.png"], "question": "What visual defect does this image exhibit?\nA.blur\nB.image stretching\nC.color distortion\nD.missing tiles", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "633bd351-a7a5-401b-97f7-d6b065f82b62", "images": ["Perception/single/633bd351-a7a5-401b-97f7-d6b065f82b62_0.png"], "question": "What is the main cause of degradation in this image?\nA.cloud\nB.image compression\nC.dead pixel\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "1c08ad8a-eeac-4e9f-b1ff-ac2fe3c035d3", "images": ["Perception/single/1c08ad8a-eeac-4e9f-b1ff-ac2fe3c035d3_0.png"], "question": "Does image stretching obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "a7652de2-481f-48b0-b524-e191f30d32d9", "images": ["Perception/single/a7652de2-481f-48b0-b524-e191f30d32d9_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.No distortion\nB.noise\nC.color distortion\nD.blur", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "3ed42eab-2a9f-4fb9-ae32-e083309bd4eb", "images": ["Perception/paired/3ed42eab-2a9f-4fb9-ae32-e083309bd4eb_0.png", "Perception/paired/3ed42eab-2a9f-4fb9-ae32-e083309bd4eb_1.png"], "question": "Does color distortion affect the quality of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "dc203fba-502e-43df-ba7a-6f52660fc43c", "images": ["Perception/single/dc203fba-502e-43df-ba7a-6f52660fc43c_0.png"], "question": "Is image compression the main factor in this distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "1a249819-6146-4b84-acdc-a5794a0a60af", "images": ["Perception/single/1a249819-6146-4b84-acdc-a5794a0a60af_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.sidelobe\nC.striping\nD.ghosting", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "7e768380-8101-4d4f-869a-decd6dbea368", "images": ["Perception/single/7e768380-8101-4d4f-869a-decd6dbea368_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "f4c0f802-fac5-41ff-94fb-a9b21e8daeee", "images": ["Perception/paired/f4c0f802-fac5-41ff-94fb-a9b21e8daeee_0.png", "Perception/paired/f4c0f802-fac5-41ff-94fb-a9b21e8daeee_1.png"], "question": "Compare Image 2 to Image 1 and choose the severity of distortion.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "6be86479-100d-4d40-9361-88bda22094af", "images": ["Perception/single/6be86479-100d-4d40-9361-88bda22094af_0.png"], "question": "What form of distortion is most apparent here?\nA.image stretching\nB.haze\nC.No distortion\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "a0b732c3-c68b-4e75-abcf-e5fa2474418f", "images": ["Perception/single/a0b732c3-c68b-4e75-abcf-e5fa2474418f_0.png"], "question": "Does impulse noise lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "e64d88a8-ae1b-432e-bd51-ec1c2ec3b301", "images": ["Perception/single/e64d88a8-ae1b-432e-bd51-ec1c2ec3b301_0.png"], "question": "Identify all distortions that degrade this remote sensing image from the options below.\nA. gaussian noise\nB. gaussian blur\nC. color distortion\nD. image compression", "answer": "B,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "6ab6b9d3-d77c-4a55-a7d8-14219cb487a7", "images": ["Perception/single/6ab6b9d3-d77c-4a55-a7d8-14219cb487a7_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.haze\nB.noise\nC.dead pixel\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "fb308b1c-e75f-4ddb-b9ee-346fd6bdd0c6", "images": ["Perception/single/fb308b1c-e75f-4ddb-b9ee-346fd6bdd0c6_0.png"], "question": "What type of distortion is visible here?\nA.No distortion\nB.haze\nC.image stretching\nD.image compression", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "2a426f95-39e1-4bf8-8c3c-aca6f92e403d", "images": ["Perception/paired/2a426f95-39e1-4bf8-8c3c-aca6f92e403d_0.png", "Perception/paired/2a426f95-39e1-4bf8-8c3c-aca6f92e403d_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.color distortion\nB.haze\nC.noise\nD.cloud", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "609ea72c-93b1-40cc-b91e-8a949df343b8", "images": ["Perception/paired/609ea72c-93b1-40cc-b91e-8a949df343b8_0.png", "Perception/paired/609ea72c-93b1-40cc-b91e-8a949df343b8_1.png"], "question": "What category of defect can be observed in Image 2 compared with Image 1?\nA.haze\nB.missing tiles\nC.cloud\nD.color distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a518b60a-f275-437a-9d07-b6dc07aeeea3", "images": ["Perception/single/a518b60a-f275-437a-9d07-b6dc07aeeea3_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.speckle\nC.ghosting\nD.striping", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "43e1110e-a555-4985-b818-0b52d28ed3ff", "images": ["Description/single/43e1110e-a555-4985-b818-0b52d28ed3ff_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe haze causes a significant loss of contrast and clarity, making the vegetation appear washed out and indistinct. Fine details in the texture of the vegetation are obscured, reducing the ability to discern patterns or boundaries within the landscape. The image quality is poor, with diminished visual and analytical utility.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "a29d658c-f9b3-40f5-8a91-15363618c7d8", "images": ["Perception/paired/a29d658c-f9b3-40f5-8a91-15363618c7d8_0.png", "Perception/paired/a29d658c-f9b3-40f5-8a91-15363618c7d8_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7a2ee643-bec9-4403-b2b6-82dbddc8ded9", "images": ["Perception/single/7a2ee643-bec9-4403-b2b6-82dbddc8ded9_0.png"], "question": "Is color distortion apparent in this remote sensing scene?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "6a7a87e0-c5c0-4c0c-b199-e6245f7ccdd4", "images": ["Perception/single/6a7a87e0-c5c0-4c0c-b199-e6245f7ccdd4_0.png"], "question": "Does this image contain motion blur and gaussian noise simultaneously?\nA.No\nB.Yes", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "8ba65c79-c813-4fec-ab81-3cae6aab81b3", "images": ["Perception/paired/8ba65c79-c813-4fec-ab81-3cae6aab81b3_0.png", "Perception/paired/8ba65c79-c813-4fec-ab81-3cae6aab81b3_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.color distortion\nB.image stretching\nC.dead pixel\nD.missing tiles", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ea598d5f-a990-4a6c-9522-327b17bfed2a", "images": ["Perception/single/ea598d5f-a990-4a6c-9522-327b17bfed2a_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.sidelobe\nC.striping\nD.ghosting", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "9eea64f7-4c03-458a-b4df-7ca6b52006f0", "images": ["Description/paired/9eea64f7-4c03-458a-b4df-7ca6b52006f0_0.png", "Description/paired/9eea64f7-4c03-458a-b4df-7ca6b52006f0_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains moderate impulse noise artifacts, which manifest as scattered white and black pixels disrupting the image's uniformity. Therefore, Image 1 has higher overall quality due to the absence of noise and distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "dd0a36db-e184-4308-b2d1-883e5f072df4", "images": ["Perception/single/dd0a36db-e184-4308-b2d1-883e5f072df4_0.png"], "question": "What is the main cause of degradation in this image?\nA.dead pixel\nB.color distortion\nC.noise\nD.cloud", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "64448dc8-c228-42c3-a4a7-f1b73aef412d", "images": ["Perception/single/64448dc8-c228-42c3-a4a7-f1b73aef412d_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.image stretching\nC.noise\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "a41070da-7af5-4e17-b440-594e3312508a", "images": ["Perception/single/a41070da-7af5-4e17-b440-594e3312508a_0.png"], "question": "Is impulse noise a critical issue in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "3a5fef73-da9b-4317-bd6a-8f48c19810a4", "images": ["Perception/single/3a5fef73-da9b-4317-bd6a-8f48c19810a4_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "e2b85eea-d209-46bc-904d-152d65b62300", "images": ["Description/single/e2b85eea-d209-46bc-904d-152d65b62300_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces blocky artifacts and color inconsistencies, disrupting the natural appearance of vegetation and terrain. Fine details such as the texture of forested areas and the clarity of small structures are heavily degraded, making it difficult to distinguish specific features. The image quality is poor, with significant loss of visual and analytical information.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "d174da36-d1a0-4b37-97ce-8d786593953a", "images": ["Perception/paired/d174da36-d1a0-4b37-97ce-8d786593953a_0.png", "Perception/paired/d174da36-d1a0-4b37-97ce-8d786593953a_1.png"], "question": "What visual defect stands out when contrasting the distorted image with its reference?\nA.haze\nB.No distortion\nC.color distortion\nD.cloud", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "183d0e32-444c-42f0-b811-9f543856eb75", "images": ["Perception/single/183d0e32-444c-42f0-b811-9f543856eb75_0.png"], "question": "What is the main cause of degradation in this image?\nA.noise\nB.haze\nC.cloud\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "c1cf0dec-9614-4b0d-9250-34a712637782", "images": ["Perception/single/c1cf0dec-9614-4b0d-9250-34a712637782_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "b7257e87-6294-44d9-83a0-5ecfab3b8cf3", "images": ["Perception/paired/b7257e87-6294-44d9-83a0-5ecfab3b8cf3_0.png", "Perception/paired/b7257e87-6294-44d9-83a0-5ecfab3b8cf3_1.png"], "question": "Is image compression the primary source of degradation in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "920d2a29-7fd2-420b-8829-7f18d1faf772", "images": ["Perception/single/920d2a29-7fd2-420b-8829-7f18d1faf772_0.png"], "question": "What type of distortion is visible here?\nA.missing tiles\nB.haze\nC.image compression\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "dfe160ce-a0ab-4210-b5e9-3eddc9b92081", "images": ["Perception/single/dfe160ce-a0ab-4210-b5e9-3eddc9b92081_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "b2080157-8e4c-497c-98df-f16ea6bee0a2", "images": ["Perception/paired/b2080157-8e4c-497c-98df-f16ea6bee0a2_0.png", "Perception/paired/b2080157-8e4c-497c-98df-f16ea6bee0a2_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "fdb87845-fcf1-42ae-b7a2-805b8b390ea7", "images": ["Perception/single/fdb87845-fcf1-42ae-b7a2-805b8b390ea7_0.png"], "question": "Does this image contain missing tiles?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "8d2050f8-a602-4fee-ba33-42e506733620", "images": ["Perception/single/8d2050f8-a602-4fee-ba33-42e506733620_0.png"], "question": "Can image stretching and image compression be observed at the same time in this image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e3258d0b-93cc-4d78-a94c-98d9076bdf2b", "images": ["Perception/single/e3258d0b-93cc-4d78-a94c-98d9076bdf2b_0.png"], "question": "Which distortion most significantly affects this image?\nA.No distortion\nB.dead pixel\nC.noise\nD.blur", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "34267b8d-7c23-4aa5-9f99-949aaafbac91", "images": ["Perception/single/34267b8d-7c23-4aa5-9f99-949aaafbac91_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "e71fd91d-4902-4b56-9eb4-277aa067d710", "images": ["Perception/single/e71fd91d-4902-4b56-9eb4-277aa067d710_0.png"], "question": "Which distortion most significantly affects this image?\nA.image compression\nB.color distortion\nC.image stretching\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "f88ad422-6997-4551-a7cd-042427b222e4", "images": ["Perception/single/f88ad422-6997-4551-a7cd-042427b222e4_0.png"], "question": "What is the primary type of artifact affecting this image?\nA.No distortion\nB.dead pixel\nC.image compression\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "3a338b5b-fd9a-4eb4-99e9-d86c325fb365", "images": ["Perception/single/3a338b5b-fd9a-4eb4-99e9-d86c325fb365_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "84ffcca8-b73b-435c-a45e-7df94f6c8cdd", "images": ["Perception/paired/84ffcca8-b73b-435c-a45e-7df94f6c8cdd_0.png", "Perception/paired/84ffcca8-b73b-435c-a45e-7df94f6c8cdd_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ffbc951a-1adb-44a7-9eb6-862109e9b18f", "images": ["Description/paired/ffbc951a-1adb-44a7-9eb6-862109e9b18f_0.png", "Description/paired/ffbc951a-1adb-44a7-9eb6-862109e9b18f_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains severe stripe noise artifacts, which manifest as horizontal lines and color distortions across the entire image. Image 1 has higher overall quality because it is free from the stripe noise artifacts present in Image 2.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "de43d221-728f-4d47-bbec-1bab2fed7706", "images": ["Perception/single/de43d221-728f-4d47-bbec-1bab2fed7706_0.png"], "question": "What visual defect does this image exhibit?\nA.cloud\nB.No distortion\nC.blur\nD.image stretching", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "e9fbe081-7f32-44ef-92d3-4b029cf29279", "images": ["Perception/paired/e9fbe081-7f32-44ef-92d3-4b029cf29279_0.png", "Perception/paired/e9fbe081-7f32-44ef-92d3-4b029cf29279_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.No distortion\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "60a3bc04-4f22-4e79-9198-bbf618521b0c", "images": ["Perception/single/60a3bc04-4f22-4e79-9198-bbf618521b0c_0.png"], "question": "What is the main cause of degradation in this image?\nA.noise\nB.image compression\nC.No distortion\nD.missing tiles", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "fd0e48f9-c943-416a-915a-9472464c83d8", "images": ["Perception/single/fd0e48f9-c943-416a-915a-9472464c83d8_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "e958ed57-f3e5-47ba-9c58-07ee14aa6a57", "images": ["Perception/paired/e958ed57-f3e5-47ba-9c58-07ee14aa6a57_0.png", "Perception/paired/e958ed57-f3e5-47ba-9c58-07ee14aa6a57_1.png"], "question": "Relative to the reference, which severity label (No/Slight, Moderate, Severe) best describes Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "0dea9aff-e94f-4ae0-b993-c4e2a7b61441", "images": ["Perception/single/0dea9aff-e94f-4ae0-b993-c4e2a7b61441_0.png"], "question": "What is the dominant distortion in this image?\nA.color distortion\nB.cloud\nC.haze\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "266e8b14-2cf6-4b4d-b184-6aeac4398bed", "images": ["Perception/paired/266e8b14-2cf6-4b4d-b184-6aeac4398bed_0.png", "Perception/paired/266e8b14-2cf6-4b4d-b184-6aeac4398bed_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "279d6ce8-f171-41af-8ff9-c030621ebe43", "images": ["Perception/paired/279d6ce8-f171-41af-8ff9-c030621ebe43_0.png", "Perception/paired/279d6ce8-f171-41af-8ff9-c030621ebe43_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable image compression artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "dc40b2bc-3dc3-4c68-9a92-a0f143815bc7", "images": ["Perception/single/dc40b2bc-3dc3-4c68-9a92-a0f143815bc7_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "9293fbff-540b-40f5-b7dd-7eba1106e4be", "images": ["Perception/single/9293fbff-540b-40f5-b7dd-7eba1106e4be_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "8c49fd97-244d-4555-8e1b-0a222f542631", "images": ["Perception/single/8c49fd97-244d-4555-8e1b-0a222f542631_0.png"], "question": "Does gaussian noise result in missing information?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "3da4c05b-8325-4503-8d62-4f54c151f3a2", "images": ["Perception/single/3da4c05b-8325-4503-8d62-4f54c151f3a2_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "7bd27a32-3b74-49b9-9a9b-7885f01e2ae0", "images": ["Perception/single/7bd27a32-3b74-49b9-9a9b-7885f01e2ae0_0.png"], "question": "Does haze obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "1a8c59c6-bf66-436d-b1c2-0eea2a91e802", "images": ["Perception/paired/1a8c59c6-bf66-436d-b1c2-0eea2a91e802_0.png", "Perception/paired/1a8c59c6-bf66-436d-b1c2-0eea2a91e802_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "817e1060-c827-4fd6-a847-9b6814771684", "images": ["Perception/paired/817e1060-c827-4fd6-a847-9b6814771684_0.png", "Perception/paired/817e1060-c827-4fd6-a847-9b6814771684_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "75467224-9763-47cd-b0b2-71914138c94a", "images": ["Perception/single/75467224-9763-47cd-b0b2-71914138c94a_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.image stretching\nC.dead pixel\nD.image compression", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "71a9f9fd-7a99-4a72-a8a2-f0189d83234a", "images": ["Perception/single/71a9f9fd-7a99-4a72-a8a2-f0189d83234a_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "074f68d3-fd5d-4360-b6f4-11b1140e0db2", "images": ["Perception/single/074f68d3-fd5d-4360-b6f4-11b1140e0db2_0.png"], "question": "Is image stretching present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "53688be2-aff4-4131-81cb-da41e50a1370", "images": ["Perception/single/53688be2-aff4-4131-81cb-da41e50a1370_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "21e0bc3f-7995-49c6-ab52-e4b9d8c6dfc1", "images": ["Perception/single/21e0bc3f-7995-49c6-ab52-e4b9d8c6dfc1_0.png"], "question": "Identify the main type of corruption in this image.\nA.dead pixel\nB.missing tiles\nC.No distortion\nD.haze", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "46b93b5b-dc3b-4165-ac26-8b9756e23237", "images": ["Perception/single/46b93b5b-dc3b-4165-ac26-8b9756e23237_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.cloud\nB.haze\nC.image stretching\nD.missing tiles", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "9476a990-1526-4d25-9b3e-b8e9a4c24db5", "images": ["Perception/single/9476a990-1526-4d25-9b3e-b8e9a4c24db5_0.png"], "question": "Select all types of distortions affecting this image.\nA. gaussian blur\nB. image stretching\nC. impulse noise\nD. dead pixel", "answer": "C,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "f595308b-0645-4f82-af59-631258c31a0c", "images": ["Perception/single/f595308b-0645-4f82-af59-631258c31a0c_0.png"], "question": "Is spatially correlated noise present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "baa97254-9c44-446a-88a4-4834aa920670", "images": ["Perception/paired/baa97254-9c44-446a-88a4-4834aa920670_0.png", "Perception/paired/baa97254-9c44-446a-88a4-4834aa920670_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7f09207b-f6b0-4d77-8739-72de0d0e4c24", "images": ["Perception/single/7f09207b-f6b0-4d77-8739-72de0d0e4c24_0.png"], "question": "What form of distortion is most apparent here?\nA.No distortion\nB.image stretching\nC.dead pixel\nD.color distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "3181c5d0-0139-4b8c-bc0d-7830130585ef", "images": ["Perception/paired/3181c5d0-0139-4b8c-bc0d-7830130585ef_0.png", "Perception/paired/3181c5d0-0139-4b8c-bc0d-7830130585ef_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a8528d71-039e-4f48-8667-f4bce085cac5", "images": ["Description/paired/a8528d71-039e-4f48-8667-f4bce085cac5_0.png", "Description/paired/a8528d71-039e-4f48-8667-f4bce085cac5_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong color distortion, with an unnatural purple hue affecting the entire scene and reducing the visibility of natural colors. Image 2 shows no observable distortions, with accurate and natural color representation and clear details. Image 2 has higher overall quality due to its lack of distortions and more realistic color fidelity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "a7d136ec-f5bd-4ad9-821c-f4fbd990ba38", "images": ["Perception/single/a7d136ec-f5bd-4ad9-821c-f4fbd990ba38_0.png"], "question": "What type of distortion is visible here?\nA.dead pixel\nB.blur\nC.color distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "def579ed-139c-466b-9312-5e4c1aa6e3bb", "images": ["Perception/single/def579ed-139c-466b-9312-5e4c1aa6e3bb_0.png"], "question": "Does haze obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "2185b4f3-a244-4b5e-9691-29d22df894b4", "images": ["Perception/single/2185b4f3-a244-4b5e-9691-29d22df894b4_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "026ef7df-5196-40be-ab11-cc1f83936727", "images": ["Perception/paired/026ef7df-5196-40be-ab11-cc1f83936727_0.png", "Perception/paired/026ef7df-5196-40be-ab11-cc1f83936727_1.png"], "question": "When comparing the two images, how noticeable is the distortion introduced in the degraded image?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "9a68c058-5290-4848-a2aa-16f7af32f566", "images": ["Perception/single/9a68c058-5290-4848-a2aa-16f7af32f566_0.png"], "question": "Is dead pixel visible in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "7cd81070-edc7-4b7a-af39-7c96907209f7", "images": ["Perception/single/7cd81070-edc7-4b7a-af39-7c96907209f7_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.cloud\nB.missing tiles\nC.image compression\nD.No distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "7bf52c8b-b832-4317-9158-30be9648f294", "images": ["Perception/single/7bf52c8b-b832-4317-9158-30be9648f294_0.png"], "question": "Is there haze present in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "77f647da-e690-420e-839d-97e9bdd231b5", "images": ["Perception/paired/77f647da-e690-420e-839d-97e9bdd231b5_0.png", "Perception/paired/77f647da-e690-420e-839d-97e9bdd231b5_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a55cc77b-25e1-45ef-9a8b-127791d9761b", "images": ["Description/single/a55cc77b-25e1-45ef-9a8b-127791d9761b_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe image compression introduces noticeable blocky artifacts and blurring, causing building edges and road outlines to appear soft and fragmented. The loss of fine details diminishes the clarity of urban structures and vegetation patterns, making it difficult to distinguish specific features like parking lots or individual trees. The image quality is poor, significantly impairing its usability for detailed analysis or interpretation.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "18c26f0d-1ed8-4927-813a-b7a336846ae6", "images": ["Perception/paired/18c26f0d-1ed8-4927-813a-b7a336846ae6_0.png", "Perception/paired/18c26f0d-1ed8-4927-813a-b7a336846ae6_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable image compression artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ae4acae8-fb29-47de-bbc4-75d00dd2829e", "images": ["Perception/single/ae4acae8-fb29-47de-bbc4-75d00dd2829e_0.png"], "question": "What category of distortion does this image belong to?\nA.color distortion\nB.image compression\nC.cloud\nD.dead pixel", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "0abca7fb-2d21-4c60-9296-7ea0d2ba6f45", "images": ["Perception/single/0abca7fb-2d21-4c60-9296-7ea0d2ba6f45_0.png"], "question": "Does this image contain color distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "6fa53b13-9a94-44e2-bbfa-4e8fa6d07220", "images": ["Perception/single/6fa53b13-9a94-44e2-bbfa-4e8fa6d07220_0.png"], "question": "Select all types of distortions affecting this image.\nA. dead pixel\nB. impulse noise\nC. gaussian noise\nD. cloud", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "acf7e36b-69d7-46b2-ac42-84f2c6d2950f", "images": ["Perception/paired/acf7e36b-69d7-46b2-ac42-84f2c6d2950f_0.png", "Perception/paired/acf7e36b-69d7-46b2-ac42-84f2c6d2950f_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "5d84cc97-42b0-49ed-9b2b-7b8e93525d5a", "images": ["Perception/single/5d84cc97-42b0-49ed-9b2b-7b8e93525d5a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "945c7461-5e5c-4dad-9406-fe9149628bcc", "images": ["Perception/paired/945c7461-5e5c-4dad-9406-fe9149628bcc_0.png", "Perception/paired/945c7461-5e5c-4dad-9406-fe9149628bcc_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.missing tiles\nB.haze\nC.color distortion\nD.image compression", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "9f5123dd-33ce-40be-8a57-7296ab23fe94", "images": ["Perception/single/9f5123dd-33ce-40be-8a57-7296ab23fe94_0.png"], "question": "What form of distortion is most apparent here?\nA.dead pixel\nB.noise\nC.blur\nD.haze", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "a7ef00f6-7510-4edb-bc60-921e25b2a665", "images": ["Perception/single/a7ef00f6-7510-4edb-bc60-921e25b2a665_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "6658aef1-b771-4b4c-b013-c7db9f61c298", "images": ["Perception/paired/6658aef1-b771-4b4c-b013-c7db9f61c298_0.png", "Perception/paired/6658aef1-b771-4b4c-b013-c7db9f61c298_1.png"], "question": "Based on the paired images, what is the dominant degradation in Image 2?\nA.blur\nB.No distortion\nC.cloud\nD.noise", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "30a4179c-c6c5-419d-ab74-b52b9dd5ae15", "images": ["Perception/single/30a4179c-c6c5-419d-ab74-b52b9dd5ae15_0.png"], "question": "Are gaussian noise and image stretching present together in the scene?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "0f1057a6-9b61-41a7-b9f2-94f2e176bc08", "images": ["Perception/single/0f1057a6-9b61-41a7-b9f2-94f2e176bc08_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.ghosting\nB.sidelobe\nC.speckle\nD.striping", "answer": "C", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "1d4c3ff0-d83d-4e3d-9472-8929e674b367", "images": ["Perception/single/1d4c3ff0-d83d-4e3d-9472-8929e674b367_0.png"], "question": "Can image stretching and deadline noise be observed at the same time in this image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "e0c5c85f-a1db-4993-8f9e-b4e3c4516054", "images": ["Perception/paired/e0c5c85f-a1db-4993-8f9e-b4e3c4516054_0.png", "Perception/paired/e0c5c85f-a1db-4993-8f9e-b4e3c4516054_1.png"], "question": "How would you rate the degradation severity in Image 2 compared to the reference Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "7c87bf29-cea0-470c-a591-02aec317e3d9", "images": ["Perception/single/7c87bf29-cea0-470c-a591-02aec317e3d9_0.png"], "question": "What distortion is present in the image?\nA.color distortion\nB.blur\nC.No distortion\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "aab943d7-2bf0-4e8a-bb04-932beeab45b7", "images": ["Perception/single/aab943d7-2bf0-4e8a-bb04-932beeab45b7_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.ghosting\nB.sidelobe\nC.striping\nD.speckle", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "fa630e8f-cd89-4f39-928d-8b05a217ab5d", "images": ["Perception/paired/fa630e8f-cd89-4f39-928d-8b05a217ab5d_0.png", "Perception/paired/fa630e8f-cd89-4f39-928d-8b05a217ab5d_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "f2080e30-16e1-4f21-a11c-5262a9e7b5d0", "images": ["Perception/single/f2080e30-16e1-4f21-a11c-5262a9e7b5d0_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "96e943f1-028e-4ca8-a19c-0155414d8b79", "images": ["Perception/single/96e943f1-028e-4ca8-a19c-0155414d8b79_0.png"], "question": "Does haze result in missing information?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "302dbcda-5537-439c-a473-1d8abafda587", "images": ["Perception/paired/302dbcda-5537-439c-a473-1d8abafda587_0.png", "Perception/paired/302dbcda-5537-439c-a473-1d8abafda587_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "878ac40b-ddb7-4a19-90f5-b2645d7ada92", "images": ["Perception/single/878ac40b-ddb7-4a19-90f5-b2645d7ada92_0.png"], "question": "What type of distortion is visible here?\nA.noise\nB.dead pixel\nC.image stretching\nD.blur", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "1c7057b2-2925-4cdf-a8b1-1c5dcc575bd9", "images": ["Perception/paired/1c7057b2-2925-4cdf-a8b1-1c5dcc575bd9_0.png", "Perception/paired/1c7057b2-2925-4cdf-a8b1-1c5dcc575bd9_1.png"], "question": "Given that Image 1 is the reference and Image 2 is distorted, how severe is the degradation in Image 2?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "21680c7e-f0bd-49e7-9cd7-e67d5930bdc4", "images": ["Perception/single/21680c7e-f0bd-49e7-9cd7-e67d5930bdc4_0.png"], "question": "Is the image impacted by missing tiles?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "90acc82f-ed55-42bf-aa67-6518620d8b0b", "images": ["Perception/paired/90acc82f-ed55-42bf-aa67-6518620d8b0b_0.png", "Perception/paired/90acc82f-ed55-42bf-aa67-6518620d8b0b_1.png"], "question": "Is image compression visible in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "d4c12a2d-0995-429e-ade3-9ad147eecec5", "images": ["Perception/single/d4c12a2d-0995-429e-ade3-9ad147eecec5_0.png"], "question": "Is missing tiles a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": null}}
+{"id": "5726fe1e-5b59-4eb5-a0b4-3514b669c94e", "images": ["Description/single/5726fe1e-5b59-4eb5-a0b4-3514b669c94e_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The distorted image exhibits severe speckling and pixelation, creating a noisy appearance that disrupts the visual coherence of urban structures. The dead pixel distortion obscures fine details, making it difficult to discern road networks and individual buildings, which significantly hampers interpretability. The image quality is poor, with substantial degradation affecting its usability for analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "82d94606-755d-4c4d-a9c7-647bccfd3489", "images": ["Perception/single/82d94606-755d-4c4d-a9c7-647bccfd3489_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "e53bc07f-e5eb-49a9-8bd2-fb7fc475a6ff", "images": ["Perception/single/e53bc07f-e5eb-49a9-8bd2-fb7fc475a6ff_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "be20bd58-fd40-4643-bab0-7f40a85af179", "images": ["Description/paired/be20bd58-fd40-4643-bab0-7f40a85af179_0.png", "Description/paired/be20bd58-fd40-4643-bab0-7f40a85af179_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe image compression artifacts, including blockiness and blurring, which significantly degrade the visual quality and detail of the image. Image 2 shows no observable distortions and maintains clear and sharp details throughout. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "cd0beb78-dd07-400d-9a8a-29f0b64f6f18", "images": ["Perception/single/cd0beb78-dd07-400d-9a8a-29f0b64f6f18_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "6cb28e22-d9ec-4acf-824d-29d2e1b6cd36", "images": ["Perception/paired/6cb28e22-d9ec-4acf-824d-29d2e1b6cd36_0.png", "Perception/paired/6cb28e22-d9ec-4acf-824d-29d2e1b6cd36_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.image compression\nB.color distortion\nC.image stretching\nD.dead pixel", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "666e47fa-2c07-4440-9077-cffbcc22eb06", "images": ["Perception/paired/666e47fa-2c07-4440-9077-cffbcc22eb06_0.png", "Perception/paired/666e47fa-2c07-4440-9077-cffbcc22eb06_1.png"], "question": "Does image compression result in missing information in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "8a786e06-8930-4eb0-8721-5e1218de4062", "images": ["Perception/single/8a786e06-8930-4eb0-8721-5e1218de4062_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "2cd7d0e8-1c31-4513-adc2-4cbf09e430f2", "images": ["Perception/paired/2cd7d0e8-1c31-4513-adc2-4cbf09e430f2_0.png", "Perception/paired/2cd7d0e8-1c31-4513-adc2-4cbf09e430f2_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "22f58c6d-5f59-48db-8a89-c59f062a3440", "images": ["Perception/single/22f58c6d-5f59-48db-8a89-c59f062a3440_0.png"], "question": "What is the dominant distortion affecting this image?\nA.haze\nB.dead pixel\nC.image compression\nD.cloud", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "69fcb087-36cb-4304-aa16-7f16c884e2c0", "images": ["Perception/single/69fcb087-36cb-4304-aa16-7f16c884e2c0_0.png"], "question": "Is stripe noise the main factor in this distortion?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "e2bfef5f-a110-4b35-a4e2-6f571170659b", "images": ["Perception/single/e2bfef5f-a110-4b35-a4e2-6f571170659b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "1b7197b7-4e1d-458e-84b3-970a0abeb0a7", "images": ["Description/paired/1b7197b7-4e1d-458e-84b3-970a0abeb0a7_0.png", "Description/paired/1b7197b7-4e1d-458e-84b3-970a0abeb0a7_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 contains severe cloud artifacts, including a bright vertical band and dense cloud cover obscuring significant portions of the terrain. Image 2 has no observable distortions and provides a clear, unobstructed view of the terrain. Image 2 has higher overall quality because it is free of artifacts and offers a more accurate representation of the scene.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": null}}
+{"id": "9d80f257-f62d-4222-9d3c-dc0cb81c1138", "images": ["Perception/paired/9d80f257-f62d-4222-9d3c-dc0cb81c1138_0.png", "Perception/paired/9d80f257-f62d-4222-9d3c-dc0cb81c1138_1.png"], "question": "Comparing to Image 1, does Image 2 contain gaussian blur?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "1827449b-144a-4241-9861-b88a9a69b98b", "images": ["Perception/single/1827449b-144a-4241-9861-b88a9a69b98b_0.png"], "question": "What category of distortion does this image belong to?\nA.noise\nB.dead pixel\nC.No distortion\nD.cloud", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "45245f44-1e58-4ac8-b564-9f6983267ad8", "images": ["Perception/single/45245f44-1e58-4ac8-b564-9f6983267ad8_0.png"], "question": "Which distortion most significantly affects this image?\nA.dead pixel\nB.blur\nC.No distortion\nD.image stretching", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "bd2bb63f-de46-4f89-bfc1-860d099edfd2", "images": ["Perception/single/bd2bb63f-de46-4f89-bfc1-860d099edfd2_0.png"], "question": "Is the image impacted by spatially correlated noise?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "e891118d-e375-4a0f-9380-0bd757663553", "images": ["Perception/paired/e891118d-e375-4a0f-9380-0bd757663553_0.png", "Perception/paired/e891118d-e375-4a0f-9380-0bd757663553_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.noise\nB.image compression\nC.image stretching\nD.missing tiles", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ff331cf5-2b25-4872-9e2e-4089147f08e5", "images": ["Perception/paired/ff331cf5-2b25-4872-9e2e-4089147f08e5_0.png", "Perception/paired/ff331cf5-2b25-4872-9e2e-4089147f08e5_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "58536b31-b78c-48b4-b717-0cffc90094da", "images": ["Perception/single/58536b31-b78c-48b4-b717-0cffc90094da_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.ghosting\nC.striping\nD.sidelobe", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "06808f67-404f-45b9-9541-cdd0ffdf080b", "images": ["Perception/paired/06808f67-404f-45b9-9541-cdd0ffdf080b_0.png", "Perception/paired/06808f67-404f-45b9-9541-cdd0ffdf080b_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "625618ae-79df-4412-87ba-69d2b2b38f7f", "images": ["Perception/paired/625618ae-79df-4412-87ba-69d2b2b38f7f_0.png", "Perception/paired/625618ae-79df-4412-87ba-69d2b2b38f7f_1.png"], "question": "Does color distortion reduce the usability of Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "5cb89db3-53e5-4104-907f-3a1a7b7fc46c", "images": ["Description/paired/5cb89db3-53e5-4104-907f-3a1a7b7fc46c_0.png", "Description/paired/5cb89db3-53e5-4104-907f-3a1a7b7fc46c_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe deadline noise artifacts, characterized by horizontal lines that disrupt the visual continuity and clarity of the image. Image 2 has no observable distortions and appears clean and high-quality. Image 2 has higher overall quality due to its lack of distortions and clearer visual presentation.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "f83a7045-242b-4b18-ae12-6b6a79b61726", "images": ["Perception/single/f83a7045-242b-4b18-ae12-6b6a79b61726_0.png"], "question": "Is the image impacted by image compression?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "6314e67a-25a5-4871-a8ea-80888afb4b49", "images": ["Perception/single/6314e67a-25a5-4871-a8ea-80888afb4b49_0.png"], "question": "What visual defect does this image exhibit?\nA.noise\nB.image compression\nC.color distortion\nD.No distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "04a52c4b-9024-4e6e-ac92-b40d86e0e521", "images": ["Perception/single/04a52c4b-9024-4e6e-ac92-b40d86e0e521_0.png"], "question": "Do visual cues of dead pixel and gaussian blur appear in the image?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "a97b2fe6-daf1-42f1-8813-4a10997737a6", "images": ["Perception/single/a97b2fe6-daf1-42f1-8813-4a10997737a6_0.png"], "question": "Identify all distortions that degrade this remote sensing image from the options below.\nA. stripe noise\nB. image stretching\nC. gaussian blur\nD. dead pixel", "answer": "A,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "52f020ca-3c24-4072-bdf6-5b4e152e24cb", "images": ["Perception/single/52f020ca-3c24-4072-bdf6-5b4e152e24cb_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.speckle\nC.striping\nD.ghosting", "answer": "B", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "ce6ba963-5f9d-4c40-b8e1-c17a9e284b56", "images": ["Perception/single/ce6ba963-5f9d-4c40-b8e1-c17a9e284b56_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.image compression\nB.image stretching\nC.cloud\nD.No distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "505e7c6b-07e4-4add-acc7-299e340c24c8", "images": ["Perception/paired/505e7c6b-07e4-4add-acc7-299e340c24c8_0.png", "Perception/paired/505e7c6b-07e4-4add-acc7-299e340c24c8_1.png"], "question": "How much quality degradation do you observe in the distorted image versus the reference?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7b87dbe7-0f34-452f-8ab2-fbb72c0f1746", "images": ["Perception/single/7b87dbe7-0f34-452f-8ab2-fbb72c0f1746_0.png"], "question": "What visual defect does this image exhibit?\nA.noise\nB.cloud\nC.missing tiles\nD.blur", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "588a484d-12ea-4a1a-88cc-95eaf0401a36", "images": ["Perception/paired/588a484d-12ea-4a1a-88cc-95eaf0401a36_0.png", "Perception/paired/588a484d-12ea-4a1a-88cc-95eaf0401a36_1.png"], "question": "Assess the overall quality of Image 2 relative to Image 1 using the three labeled categories.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "8bb6222d-237d-4767-96f5-fd341608e339", "images": ["Description/single/8bb6222d-237d-4767-96f5-fd341608e339_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe dead pixel distortion creates a noisy and grainy appearance, obscuring fine details and disrupting visual coherence.  \nKey features such as roads and vegetation textures are heavily degraded, making it difficult to interpret land use or identify specific patterns.  \nThe image quality is poor, significantly limiting its usability for analysis or decision-making.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": null}}
+{"id": "22b36fe9-3417-455b-aaed-6d64c4a036a7", "images": ["Perception/single/22b36fe9-3417-455b-aaed-6d64c4a036a7_0.png"], "question": "Which of the following distortions are present in this image? (Select all that apply)\nA. color distortion\nB. gaussian noise\nC. image stretching\nD. cloud", "answer": "B,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "bae71be4-524a-4ac9-8a59-02db16ecbcc4", "images": ["Perception/single/bae71be4-524a-4ac9-8a59-02db16ecbcc4_0.png"], "question": "What category of distortion does this image belong to?\nA.haze\nB.image compression\nC.color distortion\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "1d4f7d2d-fb09-4bcf-95d8-da9f3562513e", "images": ["Perception/single/1d4f7d2d-fb09-4bcf-95d8-da9f3562513e_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "e81a2697-89ab-4dac-a350-53af67507b3d", "images": ["Perception/single/e81a2697-89ab-4dac-a350-53af67507b3d_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.cloud\nB.image compression\nC.No distortion\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "a4839603-1cc6-480f-ad2a-ab9959dc1559", "images": ["Description/paired/a4839603-1cc6-480f-ad2a-ab9959dc1559_0.png", "Description/paired/a4839603-1cc6-480f-ad2a-ab9959dc1559_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and sharp. Image 2 contains severe Gaussian blur artifacts, making the details appear soft and indistinct. Therefore, Image 1 has higher overall quality due to its clarity and lack of distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "10da5a12-cdc6-4029-9867-b282f5d10b3d", "images": ["Perception/single/10da5a12-cdc6-4029-9867-b282f5d10b3d_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.No distortion\nB.image compression\nC.blur\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "cc956387-088a-45cf-8f25-2256f22fa4c7", "images": ["Perception/single/cc956387-088a-45cf-8f25-2256f22fa4c7_0.png"], "question": "Does image stretching obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "b53f224a-85e9-40bb-8084-5fdedf2f1615", "images": ["Perception/single/b53f224a-85e9-40bb-8084-5fdedf2f1615_0.png"], "question": "Do visual cues of cloud and image stretching appear in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "937da8d3-494e-4d66-88bf-0bc5fa8dbc9f", "images": ["Perception/single/937da8d3-494e-4d66-88bf-0bc5fa8dbc9f_0.png"], "question": "Select all types of distortions affecting this image.\nA. stripe noise\nB. dead pixel\nC. image compression\nD. spatially correlated noise", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "eaddb988-b13a-4b9f-993e-48d6c32a98d8", "images": ["Perception/single/eaddb988-b13a-4b9f-993e-48d6c32a98d8_0.png"], "question": "Is there speckle noise present in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "whether", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "3e4581eb-06fe-49b5-8a7a-ba06c1973ac0", "images": ["Perception/paired/3e4581eb-06fe-49b5-8a7a-ba06c1973ac0_0.png", "Perception/paired/3e4581eb-06fe-49b5-8a7a-ba06c1973ac0_1.png"], "question": "Does missing tiles result in missing information in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_tilesmiss", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "7b656ba0-5c34-4044-9f11-03659087e7d7", "images": ["Perception/paired/7b656ba0-5c34-4044-9f11-03659087e7d7_0.png", "Perception/paired/7b656ba0-5c34-4044-9f11-03659087e7d7_1.png"], "question": "Which distortion type most likely affects Image 2 relative to Image 1?\nA.image compression\nB.color distortion\nC.dead pixel\nD.haze", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "65bcdb5c-08c7-4032-9e59-d9d7b6b0f412", "images": ["Perception/paired/65bcdb5c-08c7-4032-9e59-d9d7b6b0f412_0.png", "Perception/paired/65bcdb5c-08c7-4032-9e59-d9d7b6b0f412_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.missing tiles\nB.image compression\nC.No distortion\nD.cloud", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "eab13a7e-7e06-4dde-b655-de15c502a490", "images": ["Perception/paired/eab13a7e-7e06-4dde-b655-de15c502a490_0.png", "Perception/paired/eab13a7e-7e06-4dde-b655-de15c502a490_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "899f7020-82ed-47e3-8b1b-9ac1605cc274", "images": ["Description/single/899f7020-82ed-47e3-8b1b-9ac1605cc274_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "The severe color distortion gives the image a strong blue-green tint, making natural and urban features appear unnatural and less distinguishable. This distortion obscures fine details, such as vegetation patterns and building materials, reducing the clarity of roads and infrastructure layouts. The image quality is poor, significantly limiting its usability for accurate interpretation or analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "59973b74-4c87-406f-94f2-1542a194b54f", "images": ["Perception/single/59973b74-4c87-406f-94f2-1542a194b54f_0.png"], "question": "What category of distortion does this image belong to?\nA.dead pixel\nB.noise\nC.image compression\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "b0e07f14-cdbb-49eb-b9de-ef8492bf7460", "images": ["Description/paired/b0e07f14-cdbb-49eb-b9de-ef8492bf7460_0.png", "Description/paired/b0e07f14-cdbb-49eb-b9de-ef8492bf7460_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits moderate spatially correlated noise artifacts, which manifest as a grainy texture and reduced clarity in the finer details of the terrain and structures. Image 2 shows no observable distortions and maintains clear and sharp details throughout. Therefore, Image 2 has higher overall quality due to its lack of noise and superior clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "acef3a08-8d62-437d-a730-8b116f23aa14", "images": ["Perception/single/acef3a08-8d62-437d-a730-8b116f23aa14_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "cd2c1264-e5fe-48d4-af2a-74d977fa3471", "images": ["Perception/single/cd2c1264-e5fe-48d4-af2a-74d977fa3471_0.png"], "question": "Does image compression affect the image quality?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "f4791e69-ca60-4672-9a9a-d13b05eb99e1", "images": ["Perception/single/f4791e69-ca60-4672-9a9a-d13b05eb99e1_0.png"], "question": "Is color distortion the primary source of degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "44986fd0-1d4f-41dd-b622-6792c54409cf", "images": ["Perception/single/44986fd0-1d4f-41dd-b622-6792c54409cf_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "3d09e52c-afae-40ac-af82-0d4f52e0602d", "images": ["Perception/single/3d09e52c-afae-40ac-af82-0d4f52e0602d_0.png"], "question": "Is gaussian blur the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "8d555828-1600-48b5-a7ab-da519ae94dfb", "images": ["Perception/single/8d555828-1600-48b5-a7ab-da519ae94dfb_0.png"], "question": "Can image compression be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "52e8d764-43d7-4018-98db-805d6dc34fa3", "images": ["Perception/single/52e8d764-43d7-4018-98db-805d6dc34fa3_0.png"], "question": "Which distortion most significantly affects this image?\nA.missing tiles\nB.color distortion\nC.dead pixel\nD.image stretching", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "6331ec1e-01c2-4f6f-a0c4-98d99863ff2f", "images": ["Perception/single/6331ec1e-01c2-4f6f-a0c4-98d99863ff2f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "a7e06f2c-c95a-48df-ac06-0ae9961b6a03", "images": ["Perception/single/a7e06f2c-c95a-48df-ac06-0ae9961b6a03_0.png"], "question": "Does spatially correlated noise result in missing information?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "4bf1c1b4-8be8-42e4-b203-075d1154ab65", "images": ["Perception/paired/4bf1c1b4-8be8-42e4-b203-075d1154ab65_0.png", "Perception/paired/4bf1c1b4-8be8-42e4-b203-075d1154ab65_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "28f33570-9c78-4e7f-adaa-75aa3017943b", "images": ["Perception/paired/28f33570-9c78-4e7f-adaa-75aa3017943b_0.png", "Perception/paired/28f33570-9c78-4e7f-adaa-75aa3017943b_1.png"], "question": "When Image 1 is treated as pristine, what distortion is visible in Image 2?\nA.blur\nB.missing tiles\nC.image compression\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "c87a9505-5a68-4bbd-8a40-8ef5920657f9", "images": ["Perception/single/c87a9505-5a68-4bbd-8a40-8ef5920657f9_0.png"], "question": "Can dead pixel and spatially correlated noise be observed at the same time in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "2231ca4f-0b6a-49e0-82aa-6e9e24d90c52", "images": ["Description/single/2231ca4f-0b6a-49e0-82aa-6e9e24d90c52_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Black horizontal bands caused by dead pixels disrupt the continuity of the urban landscape, creating visual interruptions that obscure details. These distortions hinder the ability to discern fine features such as road networks and building layouts, reducing the image's usability for detailed analysis. The image quality is moderately degraded, with noticeable artifacts impacting its overall clarity.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "581218e8-816a-4cc8-b990-d1573115962d", "images": ["Perception/single/581218e8-816a-4cc8-b990-d1573115962d_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.dead pixel\nB.missing tiles\nC.image compression\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "0e9fd4a2-2c43-4c99-a08a-93dea9e2f5b8", "images": ["Perception/paired/0e9fd4a2-2c43-4c99-a08a-93dea9e2f5b8_0.png", "Perception/paired/0e9fd4a2-2c43-4c99-a08a-93dea9e2f5b8_1.png"], "question": "Which distortion category describes the changes from Image 1 to Image 2?\nA.missing tiles\nB.noise\nC.image compression\nD.haze", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "02e7de8e-7113-47a6-961f-bc1bbc08022e", "images": ["Perception/paired/02e7de8e-7113-47a6-961f-bc1bbc08022e_0.png", "Perception/paired/02e7de8e-7113-47a6-961f-bc1bbc08022e_1.png"], "question": "Compared with Image 1, does Image 2 reveal visible quality degradation?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "e87c49ad-0e70-48a8-adde-c771424a02c2", "images": ["Perception/single/e87c49ad-0e70-48a8-adde-c771424a02c2_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.ghosting\nC.striping\nD.speckle", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "57847689-22bf-45e9-b2fd-addd583d520b", "images": ["Perception/paired/57847689-22bf-45e9-b2fd-addd583d520b_0.png", "Perception/paired/57847689-22bf-45e9-b2fd-addd583d520b_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable dead pixel artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_blind_flickering", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a337283c-dec7-43e8-a930-f539ed1a9eac", "images": ["Perception/single/a337283c-dec7-43e8-a930-f539ed1a9eac_0.png"], "question": "What specific degradation is observed in this satellite image?\nA.dead pixel\nB.haze\nC.noise\nD.missing tiles", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "0efa529a-f934-47e8-81d1-9eaf8cdb3128", "images": ["Perception/single/0efa529a-f934-47e8-81d1-9eaf8cdb3128_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.blur\nC.haze\nD.dead pixel", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "bbd41ff6-4519-4941-93db-52d9932e1e6d", "images": ["Perception/single/bbd41ff6-4519-4941-93db-52d9932e1e6d_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "0dfcbc79-fd8c-4813-93d0-3a7ff14d0035", "images": ["Perception/single/0dfcbc79-fd8c-4813-93d0-3a7ff14d0035_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.ghosting\nB.striping\nC.speckle\nD.sidelobe", "answer": "D", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "a16d4628-c315-46dd-aee2-c753201edfde", "images": ["Perception/single/a16d4628-c315-46dd-aee2-c753201edfde_0.png"], "question": "Are image compression and gaussian noise present together in the scene?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "6a500be9-92a1-4744-b35b-41621267dfaf", "images": ["Perception/single/6a500be9-92a1-4744-b35b-41621267dfaf_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.speckle\nB.ghosting\nC.striping\nD.sidelobe", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "643f6ac3-d091-47ed-a083-92a6eeddd5d1", "images": ["Perception/single/643f6ac3-d091-47ed-a083-92a6eeddd5d1_0.png"], "question": "Identify the main type of corruption in this image.\nA.noise\nB.No distortion\nC.blur\nD.image compression", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "7ba991c5-6939-4e1b-af1d-f5f2ece3f4bc", "images": ["Perception/paired/7ba991c5-6939-4e1b-af1d-f5f2ece3f4bc_0.png", "Perception/paired/7ba991c5-6939-4e1b-af1d-f5f2ece3f4bc_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "45c19ae9-0285-4578-a257-82b570b1753f", "images": ["Perception/paired/45c19ae9-0285-4578-a257-82b570b1753f_0.png", "Perception/paired/45c19ae9-0285-4578-a257-82b570b1753f_1.png"], "question": "When comparing the two images, how noticeable is the distortion introduced in the degraded image?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "a23d8c3a-e221-4550-b281-2cb29001972c", "images": ["Perception/single/a23d8c3a-e221-4550-b281-2cb29001972c_0.png"], "question": "What visual defect does this image exhibit?\nA.cloud\nB.image compression\nC.blur\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "20428e1f-5275-4fcb-a511-47c2f82c8945", "images": ["Perception/single/20428e1f-5275-4fcb-a511-47c2f82c8945_0.png"], "question": "Is image stretching present and significant?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "13b8df3a-1cbc-4259-89f4-13c00a3c2b1a", "images": ["Perception/single/13b8df3a-1cbc-4259-89f4-13c00a3c2b1a_0.png"], "question": "Identify the main type of corruption in this image.\nA.cloud\nB.No distortion\nC.blur\nD.noise", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "6819d07d-73a5-49e5-8839-8be25cfff80a", "images": ["Perception/single/6819d07d-73a5-49e5-8839-8be25cfff80a_0.png"], "question": "What visual defect does this image exhibit?\nA.cloud\nB.No distortion\nC.image compression\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_real", "distortion_complexity": "single", "comparison": null}}
+{"id": "5a0fa03a-6a44-46c6-93b1-d421d402e605", "images": ["Perception/paired/5a0fa03a-6a44-46c6-93b1-d421d402e605_0.png", "Perception/paired/5a0fa03a-6a44-46c6-93b1-d421d402e605_1.png"], "question": "Between the two images, does Image 2 display obvious distortion compared to Image 1?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "d2765e4c-7d60-4757-9583-7b154385690a", "images": ["Perception/single/d2765e4c-7d60-4757-9583-7b154385690a_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "74f2bcb2-24bf-4b7e-b503-b445de3ac13f", "images": ["Perception/single/74f2bcb2-24bf-4b7e-b503-b445de3ac13f_0.png"], "question": "Does dead pixel reduce the usability of the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "5ca7f7de-216f-4ce3-98af-64e80c685f2e", "images": ["Description/paired/5ca7f7de-216f-4ce3-98af-64e80c685f2e_0.png", "Description/paired/5ca7f7de-216f-4ce3-98af-64e80c685f2e_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits severe spatially correlated noise artifacts, appearing as a grainy texture that significantly degrades the visual clarity of the terrain. Image 2 shows no observable distortions and maintains a clear, smooth depiction of the landscape. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior visual clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "7d2768d5-6687-4ce9-81ab-91f01697e6a0", "images": ["Perception/single/7d2768d5-6687-4ce9-81ab-91f01697e6a0_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.No distortion\nB.noise\nC.dead pixel\nD.haze", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "eb679380-7890-4a27-9bf7-997586da04f0", "images": ["Perception/paired/eb679380-7890-4a27-9bf7-997586da04f0_0.png", "Perception/paired/eb679380-7890-4a27-9bf7-997586da04f0_1.png"], "question": "Relative to Image 1, does Image 2 maintain equal or higher visual quality?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "7f3b0959-c63b-4f15-b238-abc8f7e292b1", "images": ["Perception/single/7f3b0959-c63b-4f15-b238-abc8f7e292b1_0.png"], "question": "Does stripe noise lead to information loss?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": null}}
+{"id": "db58f3ca-7709-411e-9fad-a2aeba98a56b", "images": ["Perception/single/db58f3ca-7709-411e-9fad-a2aeba98a56b_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "88c40abf-0bb0-420f-b1a3-1cd63c326505", "images": ["Perception/single/88c40abf-0bb0-420f-b1a3-1cd63c326505_0.png"], "question": "Does image compression obscure the image details?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "325d1ff4-addc-4d07-a7e9-3ebe730c97d1", "images": ["Description/paired/325d1ff4-addc-4d07-a7e9-3ebe730c97d1_0.png", "Description/paired/325d1ff4-addc-4d07-a7e9-3ebe730c97d1_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and clear. Image 2 contains strong deadline noise artifacts, visible as horizontal lines across the entire image, which significantly degrade its visual quality. Therefore, Image 1 has higher overall quality due to the absence of any distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": null}}
+{"id": "440759f6-04e8-4895-b5c0-8539f3af47f6", "images": ["Perception/single/440759f6-04e8-4895-b5c0-8539f3af47f6_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.missing tiles\nC.image compression\nD.noise", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "8c5a5527-4335-4686-b65a-0f1b9dd7f046", "images": ["Perception/single/8c5a5527-4335-4686-b65a-0f1b9dd7f046_0.png"], "question": "Does spatially correlated noise affect the image quality?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "75074a5c-1678-4023-a09e-1598d493040c", "images": ["Perception/single/75074a5c-1678-4023-a09e-1598d493040c_0.png"], "question": "What category of distortion does this image belong to?\nA.blur\nB.image compression\nC.cloud\nD.color distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "225b94a5-823b-4c3b-9eee-53f16242f661", "images": ["Perception/single/225b94a5-823b-4c3b-9eee-53f16242f661_0.png"], "question": "Is the image impacted by the combination of image compression and haze?\nA.No\nB.Yes", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "2286fbbf-ea4b-48db-b8bf-0003c73ddcd3", "images": ["Perception/single/2286fbbf-ea4b-48db-b8bf-0003c73ddcd3_0.png"], "question": "What kind of image flaw is dominant in this remote sensing observation?\nA.cloud\nB.blur\nC.dead pixel\nD.No distortion", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "8931bc7a-62ce-4595-b002-4c1993542c7c", "images": ["Perception/paired/8931bc7a-62ce-4595-b002-4c1993542c7c_0.png", "Perception/paired/8931bc7a-62ce-4595-b002-4c1993542c7c_1.png"], "question": "Considering Image 1 as pristine, does Image 2 show strong signs of gaussian blur?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "cb8a2268-8dd7-46ee-a3ca-c812a1eff356", "images": ["Description/single/cb8a2268-8dd7-46ee-a3ca-c812a1eff356_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe stripe noise introduces prominent horizontal bands across the image, disrupting the uniformity of farmland and obscuring fine details in the urban area. The distortion significantly reduces interpretability, making it difficult to discern clear boundaries between fields and diminishing the visibility of structural patterns in the settlement. The image quality is poor, with substantial degradation affecting its usability for analysis.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "6e2e5330-db24-4e53-8a61-ba4290f7303e", "images": ["Description/paired/6e2e5330-db24-4e53-8a61-ba4290f7303e_0.png", "Description/paired/6e2e5330-db24-4e53-8a61-ba4290f7303e_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 exhibits strong image compression artifacts, including noticeable blockiness and blurring, which degrade the clarity and detail of the visual information. Image 2 shows no observable distortions and maintains clear, sharp details throughout. Therefore, Image 2 has higher overall quality due to its lack of distortions and superior visual clarity.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "d361c311-ddd0-4d81-83b2-eda86c04d4f5", "images": ["Perception/paired/d361c311-ddd0-4d81-83b2-eda86c04d4f5_0.png", "Perception/paired/d361c311-ddd0-4d81-83b2-eda86c04d4f5_1.png"], "question": "Treating Image 1 as pristine, how would you rate the quality of Image 2 using the three-level scale provided?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "1c952d2e-ec94-40b7-923c-3281b907fde7", "images": ["Perception/single/1c952d2e-ec94-40b7-923c-3281b907fde7_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.ghosting\nC.striping\nD.speckle", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "c22d5837-ae12-47d9-bbe1-b2f9f97b2649", "images": ["Perception/paired/c22d5837-ae12-47d9-bbe1-b2f9f97b2649_0.png", "Perception/paired/c22d5837-ae12-47d9-bbe1-b2f9f97b2649_1.png"], "question": "Assess the distortion level in Image 2 relative to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "ff94427f-5b85-4db7-8bc6-4ba6729fb8e6", "images": ["Perception/single/ff94427f-5b85-4db7-8bc6-4ba6729fb8e6_0.png"], "question": "Can deadline noise be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "8a453815-7032-4343-9a1a-e0c05d6e3278", "images": ["Perception/single/8a453815-7032-4343-9a1a-e0c05d6e3278_0.png"], "question": "Which distortion most significantly degrades this remote sensing image?\nA.No distortion\nB.dead pixel\nC.image stretching\nD.haze", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "0d94fb02-288c-4641-b730-1198054a7cd6", "images": ["Perception/single/0d94fb02-288c-4641-b730-1198054a7cd6_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.No distortion\nB.color distortion\nC.blur\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "bb3ac9b3-55a9-479e-8269-e7d6f809b863", "images": ["Description/paired/bb3ac9b3-55a9-479e-8269-e7d6f809b863_0.png", "Description/paired/bb3ac9b3-55a9-479e-8269-e7d6f809b863_1.png"], "question": "You will see two remote sensing images labeled Image 1 and Image 2. Respond with a single paragraph containing exactly three concise sentences. Sentence one must describe the observable distortions in Image 1 and how they appear visually (state if none). Sentence two must describe the observable distortions in Image 2 and how they appear visually (state if none). Sentence three must determine which image has higher overall quality (or if they are equal) and briefly explain the reason.", "answer": "Image 1 has no observable distortions and appears visually clean and high-quality. Image 2 contains severe haze artifacts, making the image appear washed out and significantly reducing visibility and detail. Therefore, Image 1 has higher overall quality due to its clarity and lack of distortions.", "meta": {"image_count": "multi", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "2d5b2aa5-10e5-4c33-905d-ccbc7a1a4067", "images": ["Perception/single/2d5b2aa5-10e5-4c33-905d-ccbc7a1a4067_0.png"], "question": "Is image compression a dominant distortion in the image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "c58da30d-99e2-4465-8d12-74cb97e4def5", "images": ["Description/single/c58da30d-99e2-4465-8d12-74cb97e4def5_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe horizontal black bands disrupt the continuity of the terrain, creating unnatural divisions across the landscape. These distortions obscure fine details, such as subtle geological features and vegetation patterns, reducing the image's interpretability for analysis. The image quality is poor due to the prominent and pervasive dead pixel artifacts.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "missing", "distortion_type": "missing_linerdeadpixels", "distortion_complexity": "single", "comparison": null}}
+{"id": "3e776b07-dba5-474c-9332-f48fc19c8351", "images": ["Perception/single/3e776b07-dba5-474c-9332-f48fc19c8351_0.png"], "question": "What distortion is present in the image?\nA.No distortion\nB.haze\nC.color distortion\nD.image compression", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "57a552d8-ded3-4bb9-b8ef-f3923cf86719", "images": ["Perception/single/57a552d8-ded3-4bb9-b8ef-f3923cf86719_0.png"], "question": "Which distortion most significantly affects this image?\nA.haze\nB.noise\nC.image stretching\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "63022be8-023f-49b5-bae4-026bb41e64e8", "images": ["Perception/single/63022be8-023f-49b5-bae4-026bb41e64e8_0.png"], "question": "Can deadline noise be observed in this image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": null}}
+{"id": "ae3a232e-2f3c-4133-8df7-3a6ac9f9f3fb", "images": ["Perception/single/ae3a232e-2f3c-4133-8df7-3a6ac9f9f3fb_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.color distortion\nC.No distortion\nD.haze", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": null}}
+{"id": "678fef5d-07f1-4457-a2d8-ecd57291b731", "images": ["Perception/paired/678fef5d-07f1-4457-a2d8-ecd57291b731_0.png", "Perception/paired/678fef5d-07f1-4457-a2d8-ecd57291b731_1.png"], "question": "How much quality degradation do you observe in the distorted image versus the reference?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "aa292da5-7b9b-43b1-b072-119f78e18e8f", "images": ["Perception/single/aa292da5-7b9b-43b1-b072-119f78e18e8f_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.striping\nC.speckle\nD.ghosting", "answer": "A", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Sidelobe", "distortion_complexity": "single", "comparison": null}}
+{"id": "5e479be6-d73b-4815-a6d9-e490bbb6c9f9", "images": ["Perception/single/5e479be6-d73b-4815-a6d9-e490bbb6c9f9_0.png"], "question": "What is the primary distortion type in this image?\nA.image stretching\nB.noise\nC.No distortion\nD.color distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "389300ad-9716-44ec-bd53-2f80e74f48f8", "images": ["Perception/paired/389300ad-9716-44ec-bd53-2f80e74f48f8_0.png", "Perception/paired/389300ad-9716-44ec-bd53-2f80e74f48f8_1.png"], "question": "Does gaussian noise obscure details in Image 2?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_gaussian", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "562a93a1-cace-4fb8-928e-a531c0b5c989", "images": ["Perception/single/562a93a1-cace-4fb8-928e-a531c0b5c989_0.png"], "question": "Does image stretching compromise the data integrity?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_stretching", "distortion_complexity": "single", "comparison": null}}
+{"id": "4d2db29a-1001-4b6f-9b59-3be8d105630d", "images": ["Perception/single/4d2db29a-1001-4b6f-9b59-3be8d105630d_0.png"], "question": "Does this image contain image compression?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "12845cb7-3eb4-4a3f-a5d9-6b41d396dde4", "images": ["Perception/paired/12845cb7-3eb4-4a3f-a5d9-6b41d396dde4_0.png", "Perception/paired/12845cb7-3eb4-4a3f-a5d9-6b41d396dde4_1.png"], "question": "Compared to Image 1, does Image 2 look cleaner and less distorted?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "ce478002-2aff-4720-a4b8-4baeaa51aa42", "images": ["Perception/single/ce478002-2aff-4720-a4b8-4baeaa51aa42_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.haze\nB.blur\nC.missing tiles\nD.image compression", "answer": "D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg", "distortion_complexity": "single", "comparison": null}}
+{"id": "d2250954-4a75-4788-a892-ab34d8b89edf", "images": ["Perception/paired/d2250954-4a75-4788-a892-ab34d8b89edf_0.png", "Perception/paired/d2250954-4a75-4788-a892-ab34d8b89edf_1.png"], "question": "How would you rate the degradation severity in Image 2 compared to the reference Image 1?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "5eb2d966-0439-48c1-aff7-406565736e48", "images": ["Perception/single/5eb2d966-0439-48c1-aff7-406565736e48_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_SPIHT", "distortion_complexity": "single", "comparison": null}}
+{"id": "949767d0-84ea-4f31-bf50-d28448a9860f", "images": ["Perception/single/949767d0-84ea-4f31-bf50-d28448a9860f_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_stripe", "distortion_complexity": "single", "comparison": null}}
+{"id": "16d31528-8407-42e7-bcff-dc595f9ab0f4", "images": ["Perception/single/16d31528-8407-42e7-bcff-dc595f9ab0f4_0.png"], "question": "Provide an overall quality rating for this remote sensing image based on the following three levels of distortion:\nA. No/Slight distortion\nB. Moderate distortion\nC. Severe distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "2e3593e1-de4e-4151-ae71-91ba2b76c3f1", "images": ["Perception/single/2e3593e1-de4e-4151-ae71-91ba2b76c3f1_0.png"], "question": "Identify all distortions that degrade this remote sensing image from the options below.\nA. image stretching\nB. motion blur\nC. stripe noise\nD. missing tiles", "answer": "B,D", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "ee705699-fcec-4fdd-aebf-c3495eea9c7a", "images": ["Perception/single/ee705699-fcec-4fdd-aebf-c3495eea9c7a_0.png"], "question": "What is the dominant distortion in this image?\nA.image stretching\nB.blur\nC.No distortion\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandattenuation", "distortion_complexity": "single", "comparison": null}}
+{"id": "96708bbc-6f50-4d28-a2a6-410762247140", "images": ["Perception/paired/96708bbc-6f50-4d28-a2a6-410762247140_0.png", "Perception/paired/96708bbc-6f50-4d28-a2a6-410762247140_1.png"], "question": "What specific degradation differentiates the low-quality image from the reference?\nA.image stretching\nB.haze\nC.image compression\nD.color distortion", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "2e286c3a-263b-4ffe-8df0-45291f05cd4a", "images": ["Perception/single/2e286c3a-263b-4ffe-8df0-45291f05cd4a_0.png"], "question": "Does missing tiles interfere with image interpretation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "5e6eb2fe-f4d4-43a6-bdd6-bd9a0c9fd877", "images": ["Perception/paired/5e6eb2fe-f4d4-43a6-bdd6-bd9a0c9fd877_0.png", "Perception/paired/5e6eb2fe-f4d4-43a6-bdd6-bd9a0c9fd877_1.png"], "question": "Does Image 2 preserve the same clarity as Image 1?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "06056a74-5290-41dc-97fd-946fcda54bad", "images": ["Description/single/06056a74-5290-41dc-97fd-946fcda54bad_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Severe spatially correlated noise introduces a grainy texture across the image, obscuring fine details and creating uneven color patterns that disrupt visual coherence. The distortion significantly diminishes interpretability, making features like vegetation patterns and terrain contours indistinct and challenging to analyze. The image quality is poor, with critical information lost due to the pervasive noise.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "453cd2b5-53c6-44d6-a03e-ce7a54af4239", "images": ["Description/single/453cd2b5-53c6-44d6-a03e-ce7a54af4239_0.png"], "question": "You are shown a single distorted remote sensing image. Write exactly three concise sentences that describe the scene and its quality:\n1. Identify the dominant type of distortion (e.g., haze, motion blur, compression artifacts, sensor noise) and describe its visible characteristics.\n2. Explain how this distortion impairs interpretability or analytical utility, citing concrete visual consequences.\n3. Provide an overall assessment of the image quality.\n\nYour response must contain exactly three sentences, with no numbering, and must not speculate about how the image 'should' look.", "answer": "Moderate image stretching causes noticeable distortion, elongating features such as roads and water bodies, which appear unnaturally stretched and less defined. This distortion reduces interpretability by making structural details like road edges and water boundaries less distinct, complicating accurate analysis. The image quality is moderately degraded, with reduced clarity and spatial coherence.", "meta": {"image_count": "single", "modality": "RGB", "task": "description", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "b6c6f248-8ac5-488d-a0bb-a5dd4305042d", "images": ["Perception/paired/b6c6f248-8ac5-488d-a0bb-a5dd4305042d_0.png", "Perception/paired/b6c6f248-8ac5-488d-a0bb-a5dd4305042d_1.png"], "question": "Which severity level best matches the difference between the reference image and the distorted one?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "26a98c79-c40a-4bbe-8077-f267c6060a35", "images": ["Perception/single/26a98c79-c40a-4bbe-8077-f267c6060a35_0.png"], "question": "What is the primary distortion that most seriously degrades the quality of this SAR image?\nA.sidelobe\nB.ghosting\nC.striping\nD.speckle", "answer": "D", "meta": {"image_count": "single", "modality": "SAR", "task": "what", "domain": "remote_sensing", "distortion_family": "sar", "distortion_type": "Speckle", "distortion_complexity": "single", "comparison": null}}
+{"id": "dac0033b-41f9-4114-a54d-a91c48268e9e", "images": ["Perception/paired/dac0033b-41f9-4114-a54d-a91c48268e9e_0.png", "Perception/paired/dac0033b-41f9-4114-a54d-a91c48268e9e_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.image compression\nB.image stretching\nC.haze\nD.No distortion", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "cloud", "distortion_type": "cloud_simplex", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "32832b76-e3ee-4365-97fe-87a04b1cc153", "images": ["Perception/single/32832b76-e3ee-4365-97fe-87a04b1cc153_0.png"], "question": "Identify the main type of corruption in this image.\nA.No distortion\nB.missing tiles\nC.image stretching\nD.noise", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "884439bb-fb0f-475c-b019-5d70c8fd2e82", "images": ["Perception/paired/884439bb-fb0f-475c-b019-5d70c8fd2e82_0.png", "Perception/paired/884439bb-fb0f-475c-b019-5d70c8fd2e82_1.png"], "question": "Compared with Image 1 (reference), does Image 2 exhibit noticeable color distortion artifacts?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "whether", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_color_bandswitch", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "8b02cd49-4e49-471b-b08f-1aeea21bd319", "images": ["Perception/single/8b02cd49-4e49-471b-b08f-1aeea21bd319_0.png"], "question": "Is image stretching responsible for visual artifacts in the image?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_impulse", "distortion_complexity": "single", "comparison": null}}
+{"id": "3afe5192-d205-42e1-b7db-83106442fba6", "images": ["Perception/paired/3afe5192-d205-42e1-b7db-83106442fba6_0.png", "Perception/paired/3afe5192-d205-42e1-b7db-83106442fba6_1.png"], "question": "When comparing the two images, how noticeable is the distortion introduced in the degraded image?\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion", "answer": "A", "meta": {"image_count": "multi", "modality": "RGB", "task": "how", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_deadline", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "09d85e77-de6b-4730-a432-908dfc158822", "images": ["Perception/single/09d85e77-de6b-4730-a432-908dfc158822_0.png"], "question": "What category of image defect does this remote sensing image show?\nA.cloud\nB.color distortion\nC.haze\nD.No distortion", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "cloud", "distortion_type": "cloud_haze", "distortion_complexity": "single", "comparison": null}}
+{"id": "23e43022-4d1a-43c2-99bb-f9bdb24372d2", "images": ["Perception/paired/23e43022-4d1a-43c2-99bb-f9bdb24372d2_0.png", "Perception/paired/23e43022-4d1a-43c2-99bb-f9bdb24372d2_1.png"], "question": "Identify the main distortion introduced between the two images.\nA.cloud\nB.color distortion\nC.haze\nD.image compression", "answer": "D", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_jpeg2000", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "2d1ec39c-61c3-4b9a-98c3-914a55f26e02", "images": ["Perception/single/2d1ec39c-61c3-4b9a-98c3-914a55f26e02_0.png"], "question": "Which distortion most significantly affects this image?\nA.blur\nB.color distortion\nC.No distortion\nD.haze", "answer": "C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "ed5fb932-6b24-4bd1-8fb8-9b555c47b634", "images": ["Perception/paired/ed5fb932-6b24-4bd1-8fb8-9b555c47b634_0.png", "Perception/paired/ed5fb932-6b24-4bd1-8fb8-9b555c47b634_1.png"], "question": "Relative to the reference image, what distortion does the degraded image exhibit most strongly?\nA.No distortion\nB.dead pixel\nC.image compression\nD.haze", "answer": "C", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "compression", "distortion_type": "compression_webp", "distortion_complexity": "single", "comparison": "inter-temporal"}}
+{"id": "f3b1cc3d-b3a7-494c-bb2c-e417ff9b79fc", "images": ["Perception/single/f3b1cc3d-b3a7-494c-bb2c-e417ff9b79fc_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.dead pixel\nB.blur\nC.haze\nD.cloud", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "bd2976ad-6541-4934-9f8e-06b76c79e82f", "images": ["Perception/single/bd2976ad-6541-4934-9f8e-06b76c79e82f_0.png"], "question": "What type of distortion is present in this remote sensing image?\nA.No distortion\nB.blur\nC.cloud\nD.missing tiles", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "noise", "distortion_type": "noise_spatially_correlated", "distortion_complexity": "single", "comparison": null}}
+{"id": "38022474-6ae7-46b9-92af-92fe55b2d483", "images": ["Perception/single/38022474-6ae7-46b9-92af-92fe55b2d483_0.png"], "question": "Can motion blur be observed in this image?\nA.Yes\nB.No", "answer": "A", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": null}}
+{"id": "d81635c6-529f-4442-879d-8c8700768e2b", "images": ["Perception/single/d81635c6-529f-4442-879d-8c8700768e2b_0.png"], "question": "Select all types of distortions affecting this image.\nA. image stretching\nB. image compression\nC. gaussian noise\nD. haze", "answer": "B,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "bedc6711-a4dd-4462-b935-d5204e798ef9", "images": ["Perception/single/bedc6711-a4dd-4462-b935-d5204e798ef9_0.png"], "question": "What is the dominant distortion in this image?\nA.dead pixel\nB.image stretching\nC.blur\nD.missing tiles", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "remote_sensing", "distortion_family": "correction", "distortion_type": "correction_compression", "distortion_complexity": "single", "comparison": null}}
+{"id": "63e49832-4bac-478a-b71f-586d1e0fd7db", "images": ["Perception/single/63e49832-4bac-478a-b71f-586d1e0fd7db_0.png"], "question": "Select all types of distortions affecting this image.\nA. impulse noise\nB. gaussian blur\nC. image compression\nD. deadline noise", "answer": "B,C", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
+{"id": "9a47495d-54f3-4114-9810-5801817edb24", "images": ["Perception/single/9a47495d-54f3-4114-9810-5801817edb24_0.png"], "question": "Is image compression the primary source of degradation?\nA.Yes\nB.No", "answer": "B", "meta": {"image_count": "single", "modality": "RGB", "task": "whether", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_gaussian", "distortion_complexity": "single", "comparison": null}}
+{"id": "264a5a23-170a-4df8-bdb3-0cf2981d99ca", "images": ["Perception/paired/264a5a23-170a-4df8-bdb3-0cf2981d99ca_0.png", "Perception/paired/264a5a23-170a-4df8-bdb3-0cf2981d99ca_1.png"], "question": "Which type of corruption is evident when comparing Image 2 against Image 1?\nA.image stretching\nB.blur\nC.haze\nD.No distortion", "answer": "B", "meta": {"image_count": "multi", "modality": "RGB", "task": "what", "domain": "general", "distortion_family": "blur", "distortion_type": "blur_motion", "distortion_complexity": "single", "comparison": "intra-image"}}
+{"id": "58bdd9d7-47f8-4f17-9134-53c4f37077d7", "images": ["Perception/single/58bdd9d7-47f8-4f17-9134-53c4f37077d7_0.png"], "question": "Select all types of distortions affecting this image.\nA. image stretching\nB. missing tiles\nC. gaussian noise\nD. stripe noise", "answer": "A,B", "meta": {"image_count": "single", "modality": "RGB", "task": "what", "domain": "mixed", "distortion_family": "multi_distortion", "distortion_type": "multi_distortion", "distortion_complexity": "complex", "comparison": null}}
diff --git a/sample.py b/sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..4c756192d73f03f519d2f2e3b88213c2ab3825f6
--- /dev/null
+++ b/sample.py
@@ -0,0 +1,118 @@
+"""Stratified sampling of SenseBench dataset (1000 instances).
+
+Sampling strategy:
+- Preserve the original distribution of task types
+- Preserve the original distribution of image_count (single/paired)
+- Fixed random seed for reproducibility
+- Output structure: Perception/{single,paired}, Description/{single,paired}
+"""
+
+import json
+import random
+import shutil
+from pathlib import Path
+from collections import Counter
+
+SEED = 42
+N_SAMPLE = 1000
+SRC_DIR = Path("/home/anxiao/zhongchen/Sensebench/data_hf")
+DST_DIR = Path("/home/anxiao/zhongchen/Sensebench/codex_code/seleted")
+
+
+def main():
+    random.seed(SEED)
+
+    records = []
+    with open(SRC_DIR / "questions.jsonl", encoding="utf-8") as f:
+        for line in f:
+            records.append(json.loads(line))
+
+    total = len(records)
+    print(f"Total records: {total}")
+
+    # Stratify by (task_category, image_count)
+    groups = {}
+    for r in records:
+        meta = r["meta"]
+        cat = "Description" if meta["task"] == "description" else "Perception"
+        sub = "paired" if meta["image_count"] == "multi" else "single"
+        key = (cat, sub)
+        groups.setdefault(key, []).append(r)
+
+    print("\nOriginal distribution:")
+    for key in sorted(groups):
+        print(f"  {key}: {len(groups[key])} ({len(groups[key])/total*100:.1f}%)")
+
+    # Proportional sampling
+    sampled = []
+    for key in sorted(groups):
+        group = groups[key]
+        n = max(1, round(len(group) / total * N_SAMPLE))
+        sampled.extend(random.sample(group, min(n, len(group))))
+
+    if len(sampled) > N_SAMPLE:
+        sampled = random.sample(sampled, N_SAMPLE)
+    elif len(sampled) < N_SAMPLE:
+        remaining = [r for r in records if r not in sampled]
+        sampled.extend(random.sample(remaining, N_SAMPLE - len(sampled)))
+
+    random.shuffle(sampled)
+
+    # Print sampled distribution
+    sampled_counter = Counter()
+    for r in sampled:
+        meta = r["meta"]
+        cat = "Description" if meta["task"] == "description" else "Perception"
+        sub = "paired" if meta["image_count"] == "multi" else "single"
+        sampled_counter[(cat, sub)] += 1
+
+    print(f"\nSampled: {len(sampled)}")
+    print("Sampled distribution:")
+    for key in sorted(sampled_counter):
+        n = sampled_counter[key]
+        print(f"  {key}: {n} ({n/len(sampled)*100:.1f}%)")
+
+    # Create subdirs and copy images
+    for cat in ["Perception", "Description"]:
+        for sub in ["single", "paired"]:
+            (DST_DIR / cat / sub).mkdir(parents=True, exist_ok=True)
+
+    copied = set()
+    with open(DST_DIR / "questions.jsonl", "w", encoding="utf-8") as f:
+        for r in sampled:
+            meta = r["meta"]
+            cat = "Description" if meta["task"] == "description" else "Perception"
+            sub = "paired" if meta["image_count"] == "multi" else "single"
+
+            new_images = []
+            for img_rel in r["images"]:
+                img_name = Path(img_rel).name
+                new_images.append(f"{cat}/{sub}/{img_name}")
+
+                if img_name not in copied:
+                    src_img = SRC_DIR / img_rel
+                    dst_img = DST_DIR / cat / sub / img_name
+                    if src_img.exists() and not dst_img.exists():
+                        shutil.copy2(src_img, dst_img)
+                    copied.add(img_name)
+
+            r["images"] = new_images
+            f.write(json.dumps(r, ensure_ascii=False) + "\n")
+
+    # Stats
+    print("\nOutput:")
+    total_size = 0
+    for cat in ["Perception", "Description"]:
+        for sub in ["single", "paired"]:
+            d = DST_DIR / cat / sub
+            n = len(list(d.iterdir()))
+            s = sum(f.stat().st_size for f in d.iterdir()) / (1024**2)
+            total_size += s
+            print(f"  {cat}/{sub}: {n} images, {s:.1f} MB")
+    print(f"  Total: {total_size:.1f} MB")
+    print(f"  Seed: {SEED}")
+    print(f"\nOutput: {DST_DIR}")
+
+
+if __name__ == "__main__":
+    main()