| --- |
| tags: |
| - seismic |
| - random-noise |
| - denoising |
| - unet |
| - resunet |
| - dncnn |
| - attention-unet |
| - ddpm |
| - scrn |
| - pytorch |
| library_name: pytorch |
| --- |
| |
| # Random Noise Suppression Benchmark |
|
|
| Deep-learning-based random-noise attenuation on pre-stack seismic shot gathers, using SEG C3 synthetic data and synthetic Gaussian / Poisson noise injection. |
|
|
| ## Task |
|
|
| Given a clean shot gather, the benchmark first injects synthetic random noise at a specified SNR, then trains a model to directly reconstruct the clean signal: |
|
|
| ```python |
| denoised = model(noisy_input) |
| ``` |
|
|
| This is a **paired regression** task with clean-target supervision. Most models directly predict the clean gather. The DDPM variant predicts diffusion noise during training and reconstructs the clean gather through reverse sampling at evaluation / inference time. |
|
|
| ## Dataset |
|
|
| - **Source**: SEG C3 pre-stack synthetic data |
| - **Current training volume**: `SEG_45Shot_shots1-9.sgy` |
| - **Geometry**: 201 traces per shot, time sampling interval `dt = 2 ms` |
| - **Split**: Shot-level sequential `7:1:1` |
| - 7 training shots |
| - 1 validation shot |
| - 1 held-out test shot |
|
|
| ### Synthetic Noise Settings |
|
|
| - **Noise kinds**: `gaussian`, `poisson` |
| - **Default sweep in training / inference scripts**: `SNR = -5, 0, 5 dB` |
| - **Noise injection**: per-shot variance-controlled synthetic corruption |
| - **Reproducibility**: noise generation is seeded from `experiment.seed` |
|
|
| ## Model Architectures |
|
|
| - **UNet** (`unet`): classic encoder-decoder with skip connections. Base channels: 32, depth: 4. |
| - **ResUNet** (`res_unet`): U-Net with residual blocks. Base channels: 32, depth: 4. |
| - **DnCNN** (`dncnn`): residual denoising CNN with 17 layers and 64 feature channels. |
| - **Attention UNet** (`atten_unet`): U-Net with attention gates. Base channels: 32, depth: 4. |
| - **DDPM** (`ddpm`): standard conditional denoising diffusion probabilistic model with reverse sampling from Gaussian noise to the clean shot gather. |
| - **SCRN** (`SCRN`): Swin Transformer convolutional residual network adapted to the same random-noise benchmark pipeline. |
|
|
| ## Preprocessing |
|
|
| - **Amplitude correction**: spherical divergence correction is skipped by default |
| - **Normalization**: `max_abs`, per-shot |
| - **Patching**: overlapping 2D patches of size `128 x 256` (`trace x time`) |
| - **Patch overlap**: `50%` |
|
|
| Training uses patched shot gathers. Inference reloads the raw volume, applies `inference.shot_split`, injects synthetic noise, runs patch-based reconstruction, and inverse-normalizes outputs for visualization. |
|
|
| ## Repository Structure |
|
|
| ```text |
| scripts/random_noise_suppression/ |
| |- train_denoise_unet.sh |
| |- train_denoise_res_unet.sh |
| |- train_denoise_dncnn.sh |
| |- train_denoise_atten_unet.sh |
| |- train_denoise_ddpm.sh |
| |- train_denoise_SCRN.sh |
| |- inference_denoise_unet.sh |
| |- inference_denoise_res_unet.sh |
| |- inference_denoise_dncnn.sh |
| |- inference_denoise_atten_unet.sh |
| |- inference_denoise_ddpm.sh |
| |- inference_denoise_SCRN.sh |
| `- run_all_random_noise_models.sh |
| |
| configs/random_noise_suppression/ |
| |- denoise_unet.yaml |
| |- denoise_res_unet.yaml |
| |- denoise_dncnn.yaml |
| |- denoise_atten_unet.yaml |
| |- denoise_ddpm.yaml |
| `- denoise_SCRN.yaml |
| ``` |
|
|
| Each experiment directory is named by model, noise kind, SNR, and seed, for example: |
|
|
| ```text |
| random_noise_unet_base_gaussian_snr5_seed42/ |
| random_noise_dncnn_base_poisson_snr0_seed43/ |
| random_noise_ddpm_base_gaussian_snrneg5_seed44/ |
| ``` |
|
|
| ## Training Details |
|
|
| Shared benchmark defaults: |
|
|
| | Hyperparameter | Value | |
| |---|---| |
| | Loss | MSE | |
| | DDPM note | trains on diffusion-noise prediction and validates clean reconstruction after reverse sampling | |
| | Optimizer | AdamW (`lr=1e-4`, `weight_decay=1e-5`) | |
| | Scheduler | Cosine annealing (`min_lr=1e-6`) | |
| | Epochs | 200 | |
| | Gradient clipping | 1.0 | |
| | Seeds | 42, 43, 44 by default in shell sweeps | |
| | Batch size | 192 in current YAML defaults | |
|
|
| ## Usage |
|
|
| ### Train One Model Family |
|
|
| ```bash |
| bash scripts/random_noise_suppression/train_denoise_unet.sh |
| ``` |
|
|
| or |
|
|
| ```bash |
| bash scripts/random_noise_suppression/train_denoise_ddpm.sh |
| ``` |
|
|
| Each training shell script sweeps: |
|
|
| - noise kind |
| - SNR |
| - seed |
|
|
| by rewriting a temporary YAML config before calling `torchrun`. |
|
|
| ### Run Inference |
|
|
| ```bash |
| bash scripts/random_noise_suppression/inference_denoise_unet.sh |
| ``` |
|
|
| Inference outputs: |
|
|
| - per-shot metrics CSV |
| - summary JSON |
| - visualizations |
| - optional `.npy` files |
| - multi-seed mean/std aggregation JSON |
|
|
| ### Run All Model Families |
|
|
| ```bash |
| bash scripts/random_noise_suppression/run_all_random_noise_models.sh |
| ``` |
|
|
| Current total-run script executes: |
|
|
| 1. `unet` |
| 2. `dncnn` |
| 3. `res_unet` |
| 4. `atten_unet` |
| 5. `ddpm` |
|
|
| Each model is trained first, then its inference sweep is launched immediately after training finishes. |
|
|
| ## Inference Outputs |
|
|
| For each experiment, the inference directory typically contains: |
|
|
| ```text |
| inference/ |
| |- inference.log |
| |- metrics_per_shot.csv |
| |- metrics_summary.json |
| |- visualizations/ |
| `- npy/ # only when save_npy=true |
| ``` |
|
|
| ### Metrics |
|
|
| The benchmark reports: |
|
|
| - `snr` |
| - `psnr` |
| - `ssim` |
| - `mae` |
| - `mse` |
| - `rmse` |
|
|
| for three groups: |
|
|
| - **noisy**: noisy input vs clean target |
| - **denoised**: model prediction vs clean target |
| - **delta**: `denoised - noisy` |
|
|
| Metrics are computed in the **normalized domain**. Saved visualization outputs are inverse-normalized back to the original amplitude domain. |
|
|
| ## Notes |
|
|
| - This benchmark injects **synthetic random noise once per experiment** before patch extraction; it is not an epoch-wise dynamic noise augmentation setup. |
| - Shot-level inference uses the held-out test shot defined by `inference.shot_split`. |
| - Batch size and patch size may need adjustment for memory-heavy models such as DnCNN and DDPM. |
|
|
| ## References |
|
|
| - Ronneberger et al., U-Net: Convolutional Networks for Biomedical Image Segmentation, MICCAI 2015 |
| - He et al., Deep Residual Learning for Image Recognition, CVPR 2016 |
| - Zhang et al., Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising, IEEE TIP 2017 |
| - Ho et al., Denoising Diffusion Probabilistic Models, NeurIPS 2020 |
| - Song et al., Denoising Diffusion Implicit Models, ICLR 2021 |
| - Oktay et al., Attention U-Net: Learning Where to Look for the Pancreas, MIDL 2018 |
| - Gao et al., Swin Transformer for simultaneous denoising and interpolation of seismic data, Computers and Geosciences 2024 |
| - SEG C3 Velocity Model: https://wiki.seg.org/wiki/C3 |
|
|
| <!-- AUTO_RESULTS_BEGIN --> |
| ## Results |
|
|
| Mean +- std over available seeds, computed from `*_seed_stats/metrics_summary_mean_std.json`. |
| Metrics are reported in the normalized domain. `Raw (noisy)` is the synthetic noisy input before denoising. |
|
|
| ### Gaussian Noise |
|
|
| #### SNR -5 dB |
|
|
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | -5.0002+-0.0015 | 19.6663+-0.0015 | 0.2452+-0.0001 | 0.087590+-0.000018 | 0.012742+-0.000004 | 0.109772+-0.000019 | 7.141253+-0.001983 | -16.4963+-0.0037 | 0.895143+-0.000147 | 0.9649+-0.0014 | 19.586534+-0.001707 | -25.2121+-0.0006 | 12.392640+-0.004453 | -21.2482+-0.0034 | 0.261746+-0.000000 | 93.2-135.68 | 1.348721+-0.000387 | -2.5770+-0.0024 | 0.045443+-0.000000 | 22.4-50.72 | 2.688605+-0.000980 | -8.5345+-0.0029 | 0.546771+-0.000000 | 50.72-93.2 | 0.928335+-0.000212 | 0.6494+-0.0020 | 0.013773+-0.000000 | 135.68-164 | 4.927647+-0.000667 | -13.7220+-0.0003 | |
| | UNet | 7.76 | 10.7195+-0.1563 | 35.3860+-0.1563 | 0.9259+-0.0018 | 0.011759+-0.000136 | 0.000335+-0.000011 | 0.017824+-0.000299 | 0.997867+-0.006434 | 0.1203+-0.0435 | 0.249041+-0.006049 | 12.1186+-0.2084 | 1.208666+-0.010888 | -1.1381+-0.0578 | 1.100664+-0.005527 | -0.5961+-0.0145 | 0.261746+-0.000000 | 93.2-135.68 | 0.324355+-0.005573 | 9.8175+-0.1427 | 0.045443+-0.000000 | 22.4-50.72 | 0.314789+-0.012138 | 10.0814+-0.3345 | 0.546771+-0.000000 | 50.72-93.2 | 0.220129+-0.004938 | 13.1914+-0.1952 | 0.013773+-0.000000 | 135.68-164 | 0.912880+-0.010192 | 0.8134+-0.0975 | |
| | ddpm | 33.30 | 10.4113+-0.0660 | 35.0778+-0.0660 | 0.9173+-0.0017 | 0.013028+-0.000097 | 0.000342+-0.000006 | 0.018107+-0.000141 | 1.368594+-0.021672 | -0.7250+-0.0439 | 0.235601+-0.002606 | 12.6539+-0.0979 | 3.055627+-0.100169 | -5.5910+-0.1234 | 2.024153+-0.052850 | -3.0214+-0.0861 | 0.261746+-0.000000 | 93.2-135.68 | 0.327920+-0.003275 | 9.9172+-0.0638 | 0.045443+-0.000000 | 22.4-50.72 | 0.325458+-0.005267 | 9.9199+-0.1544 | 0.546771+-0.000000 | 50.72-93.2 | 0.232508+-0.001620 | 12.7753+-0.0645 | 0.013773+-0.000000 | 135.68-164 | 0.976975+-0.015684 | 0.8946+-0.0758 | |
| | unet_L | 31.04 | 10.8652+-0.0339 | 35.5317+-0.0339 | 0.9276+-0.0003 | 0.011584+-0.000020 | 0.000325+-0.000002 | 0.017549+-0.000067 | 0.988307+-0.001671 | 0.1721+-0.0081 | 0.243706+-0.001447 | 12.3051+-0.0533 | 1.174356+-0.006303 | -1.0128+-0.0718 | 1.082621+-0.003258 | -0.5216+-0.0325 | 0.261746+-0.000000 | 93.2-135.68 | 0.319594+-0.001522 | 9.9425+-0.0423 | 0.045443+-0.000000 | 22.4-50.72 | 0.297286+-0.001706 | 10.5710+-0.0535 | 0.546771+-0.000000 | 50.72-93.2 | 0.217456+-0.000797 | 13.2994+-0.0299 | 0.013773+-0.000000 | 135.68-164 | 0.899668+-0.002630 | 0.9434+-0.0260 | |
| | SCRN | 0.43 | 11.9895+-0.0046 | 36.6560+-0.0046 | 0.9357+-0.0001 | 0.010733+-0.000027 | 0.000261+-0.000000 | 0.015634+-0.000009 | 0.931359+-0.001006 | 0.6515+-0.0077 | 0.205011+-0.000081 | 13.7856+-0.0038 | 1.172032+-0.005367 | -1.1765+-0.0459 | 1.043972+-0.001522 | -0.2928+-0.0147 | 0.261746+-0.000000 | 93.2-135.68 | 0.278382+-0.000312 | 11.1373+-0.0100 | 0.045443+-0.000000 | 22.4-50.72 | 0.261736+-0.001397 | 11.6779+-0.0460 | 0.546771+-0.000000 | 50.72-93.2 | 0.201131+-0.000305 | 13.9591+-0.0124 | 0.013773+-0.000000 | 135.68-164 | 0.770965+-0.001741 | 2.3024+-0.0191 | |
| | Attention UNet | 7.85 | 10.7641+-0.0358 | 35.4305+-0.0358 | 0.9264+-0.0004 | 0.011651+-0.000062 | 0.000332+-0.000004 | 0.017748+-0.000088 | 0.994784+-0.010052 | 0.1514+-0.0358 | 0.247637+-0.001390 | 12.1621+-0.0517 | 1.205975+-0.058547 | -1.0690+-0.1426 | 1.094217+-0.026710 | -0.5452+-0.0909 | 0.313958+-0.000000 | 93.2-135.68 | 0.326951+-0.001354 | 9.7390+-0.0339 | 0.055981+-0.000000 | 22.4-50.72 | 0.307575+-0.002318 | 10.2774+-0.0656 | 0.612267+-0.000000 | 50.72-93.2 | 0.219421+-0.002006 | 13.2103+-0.0819 | 0.017547+-0.000000 | 135.68-164 | 0.893144+-0.002073 | 1.0068+-0.0172 | |
| | cbdrdn | 1.49 | 11.8811+-0.0516 | 36.5476+-0.0516 | 0.9337+-0.0006 | 0.011011+-0.000062 | 0.000270+-0.000002 | 0.015899+-0.000073 | 0.940631+-0.000741 | 0.5721+-0.0100 | 0.207549+-0.001483 | 13.6693+-0.0628 | 1.205038+-0.007489 | -1.4063+-0.0629 | 1.055562+-0.001971 | -0.3717+-0.0172 | 0.313958+-0.000000 | 93.2-135.68 | 0.286780+-0.001435 | 10.8682+-0.0441 | 0.055981+-0.000000 | 22.4-50.72 | 0.258202+-0.002520 | 11.7962+-0.0871 | 0.612267+-0.000000 | 50.72-93.2 | 0.202614+-0.001119 | 13.8893+-0.0496 | 0.017547+-0.000000 | 135.68-164 | 0.768783+-0.005524 | 2.3223+-0.0634 | |
| | DnCNN | - | 11.3044+-0.0210 | 35.9709+-0.0211 | 0.9268+-0.0002 | 0.011706+-0.000019 | 0.000301+-0.000000 | 0.016818+-0.000009 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 10.7808+-0.1139 | 35.4472+-0.1140 | 0.9224+-0.0023 | 0.011804+-0.000127 | 0.000330+-0.000004 | 0.017663+-0.000148 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 12.0344+-0.0191 | 36.7008+-0.0190 | 0.9378+-0.0001 | 0.010613+-0.000035 | 0.000257+-0.000001 | 0.015509+-0.000028 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 11.0133+-0.2061 | 35.6798+-0.2061 | 0.9292+-0.0028 | 0.011366+-0.000284 | 0.000314+-0.000017 | 0.017250+-0.000447 | 0.996778+-0.010058 | 0.1706+-0.0570 | 0.237918+-0.007373 | 12.5180+-0.2815 | 1.250243+-0.083161 | -1.2594+-0.2914 | 1.116244+-0.035138 | -0.6446+-0.1393 | 0.313958+-0.000000 | 93.2-135.68 | 0.317436+-0.006913 | 10.0014+-0.1962 | 0.055981+-0.000000 | 22.4-50.72 | 0.287908+-0.009983 | 10.8528+-0.3057 | 0.612267+-0.000000 | 50.72-93.2 | 0.216799+-0.005680 | 13.3254+-0.2384 | 0.017547+-0.000000 | 135.68-164 | 0.862049+-0.014516 | 1.3152+-0.1519 | |
| | ResUNet | 8.11 | 10.5049+-0.1156 | 35.1714+-0.1156 | 0.9239+-0.0016 | 0.012144+-0.000096 | 0.000351+-0.000011 | 0.018243+-0.000275 | 1.042587+-0.020140 | -0.0514+-0.0427 | 0.255659+-0.005189 | 11.8906+-0.1802 | 1.374445+-0.089242 | -1.5841+-0.1485 | 1.186240+-0.045083 | -0.8393+-0.0956 | 0.313958+-0.000000 | 93.2-135.68 | 0.337261+-0.002697 | 9.4798+-0.0741 | 0.055981+-0.000000 | 22.4-50.72 | 0.308697+-0.010686 | 10.2523+-0.3001 | 0.612267+-0.000000 | 50.72-93.2 | 0.226527+-0.005472 | 12.9440+-0.2161 | 0.017547+-0.000000 | 135.68-164 | 0.912758+-0.007296 | 0.8404+-0.0573 | |
| | unet_plusplus | - | 11.0445+-0.1367 | 35.7109+-0.1368 | 0.9285+-0.0019 | 0.011459+-0.000146 | 0.000313+-0.000007 | 0.017203+-0.000217 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| |
| #### SNR 0 dB |
| |
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | -0.0001+-0.0015 | 24.6663+-0.0015 | 0.4878+-0.0001 | 0.049255+-0.000010 | 0.004029+-0.000001 | 0.061729+-0.000011 | 4.015822+-0.001115 | -11.4963+-0.0037 | 0.503376+-0.000083 | 5.9649+-0.0014 | 11.014318+-0.000960 | -20.2121+-0.0006 | 6.968893+-0.002505 | -16.2482+-0.0034 | 0.261746+-0.000000 | 93.2-135.68 | 0.758442+-0.000218 | 2.4230+-0.0024 | 0.045443+-0.000000 | 22.4-50.72 | 1.511914+-0.000551 | -3.5345+-0.0029 | 0.546771+-0.000000 | 50.72-93.2 | 0.522041+-0.000119 | 5.6494+-0.0020 | 0.013773+-0.000000 | 135.68-164 | 2.771020+-0.000375 | -8.7220+-0.0003 | |
| | UNet | 7.76 | 12.7346+-0.1951 | 37.4010+-0.1952 | 0.9491+-0.0020 | 0.009668+-0.000175 | 0.000209+-0.000008 | 0.014091+-0.000279 | 0.896164+-0.036976 | 1.1717+-0.2068 | 0.185054+-0.005018 | 14.7333+-0.2203 | 1.235803+-0.076864 | -1.1904+-0.1697 | 1.078681+-0.055029 | -0.2814+-0.1699 | 0.261746+-0.000000 | 93.2-135.68 | 0.255536+-0.006100 | 11.9018+-0.1912 | 0.045443+-0.000000 | 22.4-50.72 | 0.252919+-0.009483 | 11.9865+-0.3156 | 0.546771+-0.000000 | 50.72-93.2 | 0.165703+-0.002298 | 15.6865+-0.1048 | 0.013773+-0.000000 | 135.68-164 | 0.791488+-0.024628 | 2.0925+-0.2399 | |
| | ddpm | 33.30 | 12.3782+-0.0439 | 37.0446+-0.0439 | 0.9424+-0.0025 | 0.010761+-0.000053 | 0.000213+-0.000002 | 0.014344+-0.000078 | 1.220692+-0.018537 | 0.5474+-0.0252 | 0.170220+-0.001650 | 15.5654+-0.1054 | 2.947992+-0.090563 | -5.2884+-0.1205 | 1.913195+-0.046361 | -2.4205+-0.0767 | 0.261746+-0.000000 | 93.2-135.68 | 0.262120+-0.002547 | 11.9503+-0.0471 | 0.045443+-0.000000 | 22.4-50.72 | 0.271539+-0.003131 | 11.5791+-0.0900 | 0.546771+-0.000000 | 50.72-93.2 | 0.175579+-0.001547 | 15.2741+-0.0875 | 0.013773+-0.000000 | 135.68-164 | 0.835314+-0.014539 | 2.4360+-0.0679 | |
| | unet_L | 31.04 | 13.1302+-0.0421 | 37.7966+-0.0421 | 0.9528+-0.0005 | 0.009257+-0.000030 | 0.000192+-0.000002 | 0.013496+-0.000069 | 0.860230+-0.002688 | 1.4356+-0.0293 | 0.174275+-0.000943 | 15.2470+-0.0454 | 1.196778+-0.027489 | -1.1547+-0.0703 | 1.047560+-0.011152 | -0.1821+-0.0242 | 0.261746+-0.000000 | 93.2-135.68 | 0.245853+-0.001158 | 12.2270+-0.0394 | 0.045443+-0.000000 | 22.4-50.72 | 0.230874+-0.001763 | 12.7761+-0.0603 | 0.546771+-0.000000 | 50.72-93.2 | 0.161410+-0.001069 | 15.9067+-0.0573 | 0.013773+-0.000000 | 135.68-164 | 0.745971+-0.004451 | 2.6001+-0.0584 | |
| | SCRN | 0.43 | 14.3780+-0.0063 | 39.0444+-0.0063 | 0.9596+-0.0001 | 0.008325+-0.000009 | 0.000150+-0.000000 | 0.011852+-0.000007 | 0.781371+-0.000106 | 2.1940+-0.0013 | 0.143169+-0.000166 | 16.9167+-0.0101 | 1.113363+-0.007140 | -0.7756+-0.0483 | 0.967994+-0.003555 | 0.3525+-0.0274 | 0.261746+-0.000000 | 93.2-135.68 | 0.214374+-0.000153 | 13.4017+-0.0061 | 0.045443+-0.000000 | 22.4-50.72 | 0.200084+-0.000035 | 14.0094+-0.0018 | 0.546771+-0.000000 | 50.72-93.2 | 0.148425+-0.000315 | 16.6039+-0.0178 | 0.013773+-0.000000 | 135.68-164 | 0.613330+-0.000774 | 4.2929+-0.0099 | |
| | Attention UNet | 7.85 | 12.7975+-0.1023 | 37.4640+-0.1023 | 0.9496+-0.0008 | 0.009551+-0.000068 | 0.000205+-0.000003 | 0.013976+-0.000122 | 0.877201+-0.013612 | 1.2616+-0.0918 | 0.183302+-0.002576 | 14.8186+-0.1036 | 1.208193+-0.056045 | -1.2116+-0.1987 | 1.048117+-0.025011 | -0.2039+-0.1140 | 0.313958+-0.000000 | 93.2-135.68 | 0.256986+-0.002946 | 11.8432+-0.0886 | 0.055981+-0.000000 | 22.4-50.72 | 0.246047+-0.004483 | 12.2246+-0.1497 | 0.612267+-0.000000 | 50.72-93.2 | 0.165477+-0.001621 | 15.6950+-0.0693 | 0.017547+-0.000000 | 135.68-164 | 0.758715+-0.010270 | 2.4403+-0.1097 | |
| | cbdrdn | 1.49 | 13.5817+-0.4451 | 38.2482+-0.4451 | 0.9517+-0.0040 | 0.009367+-0.000495 | 0.000179+-0.000015 | 0.012960+-0.000576 | 0.833781+-0.025136 | 1.6669+-0.2422 | 0.159114+-0.009783 | 16.0194+-0.5309 | 1.225497+-0.062357 | -1.4679+-0.3471 | 1.014990+-0.024890 | 0.0313+-0.1505 | 0.313958+-0.000000 | 93.2-135.68 | 0.236191+-0.011278 | 12.5668+-0.4167 | 0.055981+-0.000000 | 22.4-50.72 | 0.219351+-0.014684 | 13.2331+-0.5934 | 0.612267+-0.000000 | 50.72-93.2 | 0.160709+-0.006907 | 15.9222+-0.3728 | 0.017547+-0.000000 | 135.68-164 | 0.670160+-0.040070 | 3.5321+-0.5323 | |
| | DnCNN | - | 13.8650+-0.0757 | 38.5314+-0.0757 | 0.9551+-0.0005 | 0.008980+-0.000068 | 0.000167+-0.000002 | 0.012521+-0.000085 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 13.3848+-0.0201 | 38.0513+-0.0201 | 0.9526+-0.0004 | 0.009171+-0.000029 | 0.000184+-0.000001 | 0.013160+-0.000039 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 14.3225+-0.0089 | 38.9890+-0.0089 | 0.9604+-0.0001 | 0.008301+-0.000004 | 0.000150+-0.000000 | 0.011866+-0.000003 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 13.0822+-0.0766 | 37.7486+-0.0766 | 0.9522+-0.0002 | 0.009239+-0.000066 | 0.000193+-0.000002 | 0.013543+-0.000084 | 0.886668+-0.013420 | 1.3442+-0.0591 | 0.175491+-0.002024 | 15.1919+-0.0900 | 1.289096+-0.047669 | -1.3235+-0.0782 | 1.092863+-0.022911 | -0.2716+-0.0687 | 0.313958+-0.000000 | 93.2-135.68 | 0.250600+-0.001527 | 12.0690+-0.0537 | 0.055981+-0.000000 | 22.4-50.72 | 0.230664+-0.004190 | 12.7771+-0.1515 | 0.612267+-0.000000 | 50.72-93.2 | 0.163923+-0.000779 | 15.7753+-0.0373 | 0.017547+-0.000000 | 135.68-164 | 0.722728+-0.002998 | 2.8827+-0.0522 | |
| | ResUNet | 8.11 | 12.5609+-0.1114 | 37.2274+-0.1114 | 0.9483+-0.0010 | 0.010003+-0.000135 | 0.000217+-0.000005 | 0.014361+-0.000158 | 0.923850+-0.026364 | 1.0449+-0.1229 | 0.188743+-0.002455 | 14.5506+-0.1086 | 1.354253+-0.089146 | -1.5437+-0.1686 | 1.132371+-0.049233 | -0.4390+-0.1342 | 0.313958+-0.000000 | 93.2-135.68 | 0.264870+-0.003472 | 11.5891+-0.1088 | 0.055981+-0.000000 | 22.4-50.72 | 0.244689+-0.004675 | 12.2700+-0.1660 | 0.612267+-0.000000 | 50.72-93.2 | 0.168409+-0.001640 | 15.5348+-0.0796 | 0.017547+-0.000000 | 135.68-164 | 0.787876+-0.014758 | 2.1512+-0.1437 | |
| | unet_plusplus | - | 13.4745+-0.0416 | 38.1409+-0.0417 | 0.9543+-0.0004 | 0.008972+-0.000037 | 0.000179+-0.000001 | 0.012988+-0.000029 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
|
|
| #### SNR 5 dB |
|
|
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | 4.9999+-0.0015 | 29.6663+-0.0015 | 0.7411+-0.0001 | 0.027698+-0.000005 | 0.001274+-0.000000 | 0.034713+-0.000006 | 2.258262+-0.000627 | -6.4963+-0.0037 | 0.283069+-0.000046 | 10.9649+-0.0014 | 6.193806+-0.000540 | -15.2121+-0.0006 | 3.918897+-0.001408 | -11.2482+-0.0034 | 0.261746+-0.000000 | 93.2-135.68 | 0.426503+-0.000123 | 7.4230+-0.0024 | 0.045443+-0.000000 | 22.4-50.72 | 0.850212+-0.000310 | 1.4655+-0.0029 | 0.546771+-0.000000 | 50.72-93.2 | 0.293565+-0.000067 | 10.6494+-0.0020 | 0.013773+-0.000000 | 135.68-164 | 1.558259+-0.000211 | -3.7220+-0.0003 | |
| | UNet | 7.76 | 14.8439+-0.4420 | 39.5103+-0.4420 | 0.9676+-0.0033 | 0.007730+-0.000361 | 0.000128+-0.000012 | 0.011019+-0.000540 | 0.719111+-0.034267 | 3.0424+-0.4271 | 0.138693+-0.008213 | 17.2964+-0.4823 | 1.155559+-0.043804 | -0.8769+-0.2212 | 0.946052+-0.031838 | 0.7052+-0.2676 | 0.261746+-0.000000 | 93.2-135.68 | 0.202157+-0.010179 | 13.9572+-0.4203 | 0.045443+-0.000000 | 22.4-50.72 | 0.206300+-0.014558 | 13.7798+-0.5944 | 0.546771+-0.000000 | 50.72-93.2 | 0.124741+-0.005391 | 18.1947+-0.3452 | 0.013773+-0.000000 | 135.68-164 | 0.639408+-0.031933 | 3.9624+-0.4481 | |
| | ddpm | 33.30 | 14.3109+-0.2331 | 38.9774+-0.2331 | 0.9607+-0.0031 | 0.008788+-0.000244 | 0.000133+-0.000007 | 0.011406+-0.000293 | 1.056677+-0.039264 | 2.3543+-0.1675 | 0.122586+-0.002645 | 18.5639+-0.1390 | 2.856104+-0.169225 | -4.8859+-0.3742 | 1.785473+-0.088003 | -1.4952+-0.2722 | 0.261746+-0.000000 | 93.2-135.68 | 0.210138+-0.005565 | 14.0006+-0.1760 | 0.045443+-0.000000 | 22.4-50.72 | 0.233449+-0.008681 | 13.0102+-0.2879 | 0.546771+-0.000000 | 50.72-93.2 | 0.131869+-0.002700 | 17.8682+-0.1428 | 0.013773+-0.000000 | 135.68-164 | 0.699858+-0.023049 | 4.2562+-0.1705 | |
| | unet_L | 31.04 | 15.8485+-0.0706 | 40.5150+-0.0705 | 0.9730+-0.0006 | 0.006915+-0.000052 | 0.000103+-0.000002 | 0.009869+-0.000083 | 0.657661+-0.003585 | 3.7919+-0.0552 | 0.119565+-0.001454 | 18.5468+-0.1039 | 1.095432+-0.015124 | -0.4963+-0.0516 | 0.889480+-0.006917 | 1.2051+-0.0255 | 0.261746+-0.000000 | 93.2-135.68 | 0.183340+-0.001258 | 14.7741+-0.0576 | 0.045443+-0.000000 | 22.4-50.72 | 0.174386+-0.002595 | 15.2235+-0.1282 | 0.546771+-0.000000 | 50.72-93.2 | 0.114728+-0.001854 | 18.8847+-0.1377 | 0.013773+-0.000000 | 135.68-164 | 0.555501+-0.002575 | 5.1763+-0.0387 | |
| | SCRN | 0.43 | 17.0551+-0.0123 | 41.7215+-0.0123 | 0.9773+-0.0001 | 0.006136+-0.000016 | 0.000080+-0.000000 | 0.008675+-0.000012 | 0.597121+-0.002720 | 4.5699+-0.0273 | 0.097873+-0.000050 | 20.2352+-0.0087 | 1.009696+-0.008051 | 0.0497+-0.0324 | 0.821374+-0.004438 | 1.7895+-0.0246 | 0.261746+-0.000000 | 93.2-135.68 | 0.161297+-0.000307 | 15.8690+-0.0161 | 0.045443+-0.000000 | 22.4-50.72 | 0.147763+-0.000305 | 16.6431+-0.0213 | 0.546771+-0.000000 | 50.72-93.2 | 0.104686+-0.000163 | 19.6367+-0.0169 | 0.013773+-0.000000 | 135.68-164 | 0.470543+-0.001610 | 6.5933+-0.0265 | |
| | Attention UNet | 7.85 | 14.8935+-0.2287 | 39.5599+-0.2287 | 0.9677+-0.0014 | 0.007652+-0.000174 | 0.000125+-0.000006 | 0.010927+-0.000255 | 0.714476+-0.019492 | 3.0873+-0.2011 | 0.137611+-0.004234 | 17.3756+-0.2390 | 1.153636+-0.052686 | -0.8163+-0.2427 | 0.942364+-0.029417 | 0.7435+-0.2015 | 0.313958+-0.000000 | 93.2-135.68 | 0.199831+-0.005196 | 14.0604+-0.1992 | 0.055981+-0.000000 | 22.4-50.72 | 0.204458+-0.006843 | 13.8477+-0.2867 | 0.612267+-0.000000 | 50.72-93.2 | 0.125462+-0.003045 | 18.1575+-0.1810 | 0.017547+-0.000000 | 135.68-164 | 0.607072+-0.019445 | 4.4044+-0.2685 | |
| | cbdrdn | 1.49 | 16.4587+-0.4697 | 41.1251+-0.4697 | 0.9738+-0.0024 | 0.006755+-0.000420 | 0.000092+-0.000009 | 0.009280+-0.000453 | 0.641893+-0.029979 | 3.9933+-0.3676 | 0.105119+-0.007073 | 19.6461+-0.5273 | 1.064784+-0.039411 | -0.2726+-0.2146 | 0.867990+-0.024057 | 1.3992+-0.1731 | 0.313958+-0.000000 | 93.2-135.68 | 0.172087+-0.008958 | 15.3240+-0.4269 | 0.055981+-0.000000 | 22.4-50.72 | 0.159543+-0.011129 | 15.9988+-0.5762 | 0.612267+-0.000000 | 50.72-93.2 | 0.112184+-0.005648 | 19.0541+-0.3998 | 0.017547+-0.000000 | 135.68-164 | 0.490332+-0.033179 | 6.2594+-0.5620 | |
| | DnCNN | - | 16.7481+-0.0492 | 41.4146+-0.0492 | 0.9758+-0.0002 | 0.006463+-0.000040 | 0.000085+-0.000001 | 0.008953+-0.000041 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 16.0238+-0.0359 | 40.6903+-0.0359 | 0.9728+-0.0002 | 0.006889+-0.000019 | 0.000099+-0.000001 | 0.009679+-0.000034 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 16.8336+-0.0160 | 41.5000+-0.0160 | 0.9773+-0.0000 | 0.006203+-0.000013 | 0.000083+-0.000000 | 0.008835+-0.000011 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 15.9001+-0.1500 | 40.5665+-0.1500 | 0.9733+-0.0009 | 0.006853+-0.000075 | 0.000101+-0.000003 | 0.009793+-0.000167 | 0.665246+-0.016741 | 3.7976+-0.1168 | 0.118503+-0.003065 | 18.6263+-0.2268 | 1.128243+-0.043808 | -0.5401+-0.0996 | 0.905634+-0.024093 | 1.1756+-0.0834 | 0.313958+-0.000000 | 93.2-135.68 | 0.182367+-0.002164 | 14.8233+-0.1010 | 0.055981+-0.000000 | 22.4-50.72 | 0.169854+-0.006183 | 15.4480+-0.3207 | 0.612267+-0.000000 | 50.72-93.2 | 0.114205+-0.001785 | 18.9200+-0.1366 | 0.017547+-0.000000 | 135.68-164 | 0.535691+-0.011338 | 5.5020+-0.1829 | |
| | ResUNet | 8.11 | 14.9238+-0.0496 | 39.5903+-0.0495 | 0.9694+-0.0005 | 0.007797+-0.000072 | 0.000125+-0.000001 | 0.010913+-0.000062 | 0.714624+-0.006742 | 3.1785+-0.0663 | 0.137032+-0.000565 | 17.3721+-0.0375 | 1.190168+-0.021451 | -0.9201+-0.1013 | 0.953672+-0.010687 | 0.7827+-0.0625 | 0.313958+-0.000000 | 93.2-135.68 | 0.199863+-0.000695 | 14.0371+-0.0312 | 0.055981+-0.000000 | 22.4-50.72 | 0.191987+-0.002350 | 14.3921+-0.1055 | 0.612267+-0.000000 | 50.72-93.2 | 0.121381+-0.000425 | 18.4127+-0.0270 | 0.017547+-0.000000 | 135.68-164 | 0.613098+-0.002927 | 4.3152+-0.0471 | |
| | unet_plusplus | - | 16.1852+-0.0544 | 40.8516+-0.0544 | 0.9741+-0.0003 | 0.006638+-0.000056 | 0.000095+-0.000000 | 0.009469+-0.000031 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| |
| ### Poisson Noise |
| |
| #### SNR -5 dB |
| |
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | -4.9991+-0.0009 | 19.6674+-0.0009 | 0.2452+-0.0000 | 0.087512+-0.000008 | 0.012738+-0.000003 | 0.109756+-0.000011 | 7.139934+-0.002099 | -16.4943+-0.0019 | 0.894940+-0.000218 | 0.9668+-0.0021 | 19.590212+-0.011286 | -25.2141+-0.0025 | 12.385180+-0.004828 | -21.2459+-0.0022 | 0.261746+-0.000000 | 93.2-135.68 | 1.348540+-0.000279 | -2.5756+-0.0018 | 0.045443+-0.000000 | 22.4-50.72 | 2.687388+-0.000903 | -8.5305+-0.0028 | 0.546771+-0.000000 | 50.72-93.2 | 0.928298+-0.000440 | 0.6498+-0.0042 | 0.013773+-0.000000 | 135.68-164 | 4.927557+-0.002254 | -13.7226+-0.0041 | |
| | UNet | 7.76 | 10.7209+-0.1723 | 35.3873+-0.1723 | 0.9257+-0.0021 | 0.011764+-0.000162 | 0.000334+-0.000011 | 0.017796+-0.000306 | 1.017308+-0.029620 | 0.0615+-0.1004 | 0.248659+-0.006539 | 12.1391+-0.2200 | 1.268583+-0.079916 | -1.2557+-0.1269 | 1.138946+-0.050646 | -0.6799+-0.0888 | 0.261746+-0.000000 | 93.2-135.68 | 0.324272+-0.006602 | 9.8301+-0.1620 | 0.045443+-0.000000 | 22.4-50.72 | 0.315766+-0.014219 | 10.0591+-0.3865 | 0.546771+-0.000000 | 50.72-93.2 | 0.220340+-0.004580 | 13.1915+-0.1745 | 0.013773+-0.000000 | 135.68-164 | 0.919305+-0.018875 | 0.7750+-0.1514 | |
| | ddpm | 33.30 | 10.4292+-0.0604 | 35.0956+-0.0604 | 0.9159+-0.0045 | 0.012995+-0.000098 | 0.000340+-0.000005 | 0.018075+-0.000125 | 1.359538+-0.005749 | -0.6860+-0.0459 | 0.235958+-0.001554 | 12.6393+-0.0556 | 3.005283+-0.032889 | -5.4588+-0.1388 | 1.999240+-0.014108 | -2.9275+-0.0894 | 0.261746+-0.000000 | 93.2-135.68 | 0.324534+-0.002262 | 9.9985+-0.0544 | 0.045443+-0.000000 | 22.4-50.72 | 0.325031+-0.004099 | 9.9172+-0.1134 | 0.546771+-0.000000 | 50.72-93.2 | 0.233096+-0.001255 | 12.7472+-0.0449 | 0.013773+-0.000000 | 135.68-164 | 0.970855+-0.011787 | 0.9344+-0.0556 | |
| | unet_L | 31.04 | 10.9279+-0.0485 | 35.5943+-0.0485 | 0.9276+-0.0006 | 0.011547+-0.000039 | 0.000322+-0.000003 | 0.017447+-0.000094 | 0.994088+-0.006194 | 0.1293+-0.0254 | 0.240230+-0.001885 | 12.4276+-0.0669 | 1.214256+-0.020595 | -1.2919+-0.0283 | 1.104581+-0.010721 | -0.6813+-0.0245 | 0.261746+-0.000000 | 93.2-135.68 | 0.316108+-0.001415 | 10.0362+-0.0390 | 0.045443+-0.000000 | 22.4-50.72 | 0.295328+-0.005336 | 10.6284+-0.1587 | 0.546771+-0.000000 | 50.72-93.2 | 0.218877+-0.001858 | 13.2383+-0.0749 | 0.013773+-0.000000 | 135.68-164 | 0.888299+-0.006219 | 1.0527+-0.0603 | |
| | SCRN | 0.43 | 11.9910+-0.0130 | 36.6574+-0.0130 | 0.9355+-0.0002 | 0.010745+-0.000022 | 0.000261+-0.000001 | 0.015617+-0.000018 | 0.932323+-0.002807 | 0.6476+-0.0157 | 0.204771+-0.000313 | 13.7975+-0.0134 | 1.178139+-0.008656 | -1.2097+-0.0524 | 1.046177+-0.004888 | -0.2977+-0.0191 | 0.261746+-0.000000 | 93.2-135.68 | 0.278190+-0.000143 | 11.1451+-0.0050 | 0.045443+-0.000000 | 22.4-50.72 | 0.263647+-0.001722 | 11.6156+-0.0588 | 0.546771+-0.000000 | 50.72-93.2 | 0.200993+-0.000553 | 13.9653+-0.0253 | 0.013773+-0.000000 | 135.68-164 | 0.771739+-0.001349 | 2.2939+-0.0118 | |
| | Attention UNet | 7.85 | 10.8449+-0.0674 | 35.5113+-0.0674 | 0.9273+-0.0007 | 0.011566+-0.000076 | 0.000325+-0.000007 | 0.017554+-0.000166 | 0.997249+-0.012409 | 0.1506+-0.0484 | 0.244426+-0.002909 | 12.2830+-0.1094 | 1.231557+-0.060617 | -1.1638+-0.1756 | 1.106213+-0.032185 | -0.5931+-0.1215 | 0.313958+-0.000000 | 93.2-135.68 | 0.323799+-0.002840 | 9.8272+-0.0777 | 0.055981+-0.000000 | 22.4-50.72 | 0.303853+-0.004804 | 10.3861+-0.1376 | 0.612267+-0.000000 | 50.72-93.2 | 0.217534+-0.002346 | 13.2924+-0.1006 | 0.017547+-0.000000 | 135.68-164 | 0.890297+-0.002787 | 1.0431+-0.0352 | |
| | DnCNN | - | 11.2894+-0.0302 | 35.9558+-0.0302 | 0.9264+-0.0004 | 0.011744+-0.000047 | 0.000301+-0.000002 | 0.016835+-0.000055 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 10.8567+-0.0486 | 35.5232+-0.0486 | 0.9234+-0.0009 | 0.011722+-0.000051 | 0.000326+-0.000002 | 0.017549+-0.000071 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 12.0482+-0.0143 | 36.7146+-0.0143 | 0.9377+-0.0002 | 0.010612+-0.000032 | 0.000256+-0.000000 | 0.015476+-0.000016 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 10.9369+-0.0784 | 35.6033+-0.0784 | 0.9288+-0.0014 | 0.011434+-0.000093 | 0.000314+-0.000011 | 0.017290+-0.000260 | 1.026927+-0.027208 | 0.0865+-0.0515 | 0.240938+-0.003299 | 12.4379+-0.1468 | 1.346390+-0.141938 | -1.2769+-0.3269 | 1.166573+-0.066851 | -0.6866+-0.1752 | 0.313958+-0.000000 | 93.2-135.68 | 0.320958+-0.002895 | 9.9253+-0.0915 | 0.055981+-0.000000 | 22.4-50.72 | 0.293362+-0.004376 | 10.6996+-0.1327 | 0.612267+-0.000000 | 50.72-93.2 | 0.217444+-0.003441 | 13.3289+-0.1642 | 0.017547+-0.000000 | 135.68-164 | 0.872839+-0.002358 | 1.2119+-0.0244 | |
| | ResUNet | 8.11 | 10.5332+-0.1662 | 35.1996+-0.1662 | 0.9240+-0.0019 | 0.012113+-0.000143 | 0.000348+-0.000013 | 0.018172+-0.000343 | 1.052649+-0.007407 | -0.0762+-0.0226 | 0.254369+-0.006839 | 11.9378+-0.2322 | 1.414804+-0.049493 | -1.6568+-0.1023 | 1.209814+-0.020189 | -0.8922+-0.0502 | 0.313958+-0.000000 | 93.2-135.68 | 0.335905+-0.004226 | 9.5214+-0.1075 | 0.055981+-0.000000 | 22.4-50.72 | 0.307812+-0.013181 | 10.2790+-0.3645 | 0.612267+-0.000000 | 50.72-93.2 | 0.226208+-0.007047 | 12.9601+-0.2689 | 0.017547+-0.000000 | 135.68-164 | 0.913961+-0.009352 | 0.8379+-0.0830 | |
| | unet_plusplus | - | 10.9828+-0.0946 | 35.6493+-0.0946 | 0.9281+-0.0014 | 0.011491+-0.000125 | 0.000313+-0.000006 | 0.017234+-0.000151 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
|
|
| #### SNR 0 dB |
|
|
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | 0.0010+-0.0009 | 24.6675+-0.0009 | 0.4879+-0.0000 | 0.049214+-0.000002 | 0.004028+-0.000001 | 0.061721+-0.000006 | 4.014423+-0.001113 | -11.4939+-0.0017 | 0.503434+-0.000138 | 5.9639+-0.0024 | 11.013212+-0.003360 | -20.2103+-0.0040 | 6.968074+-0.001946 | -16.2466+-0.0033 | 0.261746+-0.000000 | 93.2-135.68 | 0.758425+-0.000201 | 2.4234+-0.0023 | 0.045443+-0.000000 | 22.4-50.72 | 1.511425+-0.000256 | -3.5316+-0.0013 | 0.546771+-0.000000 | 50.72-93.2 | 0.521947+-0.000065 | 5.6510+-0.0012 | 0.013773+-0.000000 | 135.68-164 | 2.771034+-0.000318 | -8.7230+-0.0008 | |
| | UNet | 7.76 | 12.7310+-0.1923 | 37.3974+-0.1924 | 0.9490+-0.0020 | 0.009671+-0.000176 | 0.000209+-0.000008 | 0.014087+-0.000269 | 0.907593+-0.048260 | 1.1362+-0.2311 | 0.184975+-0.004740 | 14.7391+-0.2089 | 1.268607+-0.108947 | -1.2261+-0.1850 | 1.096960+-0.076684 | -0.3106+-0.2065 | 0.261746+-0.000000 | 93.2-135.68 | 0.255543+-0.006282 | 11.9096+-0.1896 | 0.045443+-0.000000 | 22.4-50.72 | 0.252930+-0.009338 | 11.9882+-0.3097 | 0.546771+-0.000000 | 50.72-93.2 | 0.166160+-0.002105 | 15.6641+-0.0946 | 0.013773+-0.000000 | 135.68-164 | 0.794646+-0.027580 | 2.0812+-0.2400 | |
| | ddpm | 33.30 | 12.3655+-0.0209 | 37.0319+-0.0208 | 0.9416+-0.0014 | 0.010781+-0.000032 | 0.000214+-0.000001 | 0.014372+-0.000031 | 1.218878+-0.008018 | 0.5442+-0.0164 | 0.170832+-0.000065 | 15.5266+-0.0104 | 2.923362+-0.038753 | -5.2182+-0.1049 | 1.903350+-0.019148 | -2.3890+-0.0622 | 0.261746+-0.000000 | 93.2-135.68 | 0.261415+-0.001326 | 11.9674+-0.0290 | 0.045443+-0.000000 | 22.4-50.72 | 0.273896+-0.000961 | 11.4861+-0.0165 | 0.546771+-0.000000 | 50.72-93.2 | 0.176148+-0.000274 | 15.2402+-0.0039 | 0.013773+-0.000000 | 135.68-164 | 0.831818+-0.007545 | 2.4574+-0.0177 | |
| | unet_L | 31.04 | 13.1325+-0.0709 | 37.7989+-0.0709 | 0.9524+-0.0003 | 0.009267+-0.000065 | 0.000192+-0.000002 | 0.013499+-0.000094 | 0.859777+-0.007079 | 1.4313+-0.0441 | 0.174137+-0.001690 | 15.2538+-0.0809 | 1.194956+-0.019472 | -1.1619+-0.0659 | 1.043909+-0.013014 | -0.1653+-0.0541 | 0.261746+-0.000000 | 93.2-135.68 | 0.245594+-0.001685 | 12.2342+-0.0563 | 0.045443+-0.000000 | 22.4-50.72 | 0.230140+-0.002141 | 12.8014+-0.0805 | 0.546771+-0.000000 | 50.72-93.2 | 0.161536+-0.000510 | 15.8998+-0.0221 | 0.013773+-0.000000 | 135.68-164 | 0.744120+-0.015267 | 2.6174+-0.1714 | |
| | SCRN | 0.43 | 14.3830+-0.0080 | 39.0494+-0.0080 | 0.9595+-0.0000 | 0.008319+-0.000011 | 0.000149+-0.000000 | 0.011838+-0.000001 | 0.782246+-0.001623 | 2.1852+-0.0078 | 0.142793+-0.000228 | 16.9429+-0.0084 | 1.117325+-0.007654 | -0.8071+-0.0239 | 0.970752+-0.005068 | 0.3335+-0.0191 | 0.261746+-0.000000 | 93.2-135.68 | 0.214182+-0.000266 | 13.4121+-0.0088 | 0.045443+-0.000000 | 22.4-50.72 | 0.200047+-0.000994 | 14.0126+-0.0386 | 0.546771+-0.000000 | 50.72-93.2 | 0.148326+-0.000204 | 16.6108+-0.0100 | 0.013773+-0.000000 | 135.68-164 | 0.615807+-0.001182 | 4.2618+-0.0167 | |
| | Attention UNet | 7.85 | 12.7997+-0.1199 | 37.4661+-0.1200 | 0.9494+-0.0007 | 0.009557+-0.000066 | 0.000205+-0.000004 | 0.013976+-0.000150 | 0.878699+-0.013720 | 1.2425+-0.0856 | 0.182951+-0.003286 | 14.8344+-0.1370 | 1.206386+-0.056424 | -1.1935+-0.1870 | 1.049687+-0.024762 | -0.2158+-0.1087 | 0.313958+-0.000000 | 93.2-135.68 | 0.256982+-0.003523 | 11.8443+-0.1067 | 0.055981+-0.000000 | 22.4-50.72 | 0.245814+-0.004581 | 12.2302+-0.1544 | 0.612267+-0.000000 | 50.72-93.2 | 0.165088+-0.001888 | 15.7117+-0.0841 | 0.017547+-0.000000 | 135.68-164 | 0.760263+-0.012105 | 2.4238+-0.1290 | |
| | DnCNN | - | 13.8524+-0.0459 | 38.5189+-0.0459 | 0.9549+-0.0004 | 0.008989+-0.000056 | 0.000168+-0.000001 | 0.012552+-0.000054 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 13.3724+-0.0078 | 38.0388+-0.0078 | 0.9525+-0.0001 | 0.009193+-0.000031 | 0.000184+-0.000000 | 0.013168+-0.000005 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 14.3409+-0.0129 | 39.0073+-0.0129 | 0.9603+-0.0001 | 0.008301+-0.000008 | 0.000149+-0.000000 | 0.011843+-0.000009 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 13.0344+-0.0612 | 37.7008+-0.0612 | 0.9519+-0.0003 | 0.009284+-0.000004 | 0.000195+-0.000002 | 0.013597+-0.000077 | 0.902603+-0.027396 | 1.2918+-0.0824 | 0.176591+-0.001545 | 15.1408+-0.0683 | 1.328422+-0.092079 | -1.3893+-0.1746 | 1.122240+-0.051963 | -0.3427+-0.1253 | 0.313958+-0.000000 | 93.2-135.68 | 0.251091+-0.000921 | 12.0508+-0.0303 | 0.055981+-0.000000 | 22.4-50.72 | 0.232529+-0.002185 | 12.7044+-0.0765 | 0.612267+-0.000000 | 50.72-93.2 | 0.163829+-0.000953 | 15.7787+-0.0449 | 0.017547+-0.000000 | 135.68-164 | 0.726786+-0.006988 | 2.8255+-0.0773 | |
| | ResUNet | 8.11 | 12.5691+-0.0935 | 37.2355+-0.0935 | 0.9482+-0.0008 | 0.010001+-0.000119 | 0.000216+-0.000004 | 0.014346+-0.000138 | 0.933495+-0.022755 | 1.0130+-0.0907 | 0.188056+-0.002229 | 14.5796+-0.0985 | 1.385053+-0.078697 | -1.6117+-0.1316 | 1.153921+-0.044341 | -0.4981+-0.1030 | 0.313958+-0.000000 | 93.2-135.68 | 0.264314+-0.002996 | 11.6117+-0.0955 | 0.055981+-0.000000 | 22.4-50.72 | 0.245076+-0.004233 | 12.2532+-0.1503 | 0.612267+-0.000000 | 50.72-93.2 | 0.168367+-0.001540 | 15.5338+-0.0759 | 0.017547+-0.000000 | 135.68-164 | 0.788946+-0.013971 | 2.1604+-0.1320 | |
| | unet_plusplus | - | 13.4932+-0.0835 | 38.1597+-0.0835 | 0.9544+-0.0006 | 0.008933+-0.000110 | 0.000178+-0.000001 | 0.012968+-0.000067 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| |
| #### SNR 5 dB |
| |
| | Method | Parameters (M) | SNR | PSNR | SSIM | MAE | MSE | RMSE | EB_WSE_MEDIUM_40_70_NE | EB_WSE_MEDIUM_40_70_SNR | EB_WSE_STRONG_70_100_NE | EB_WSE_STRONG_70_100_SNR | EB_WSE_VERY_WEAK_5_20_NE | EB_WSE_VERY_WEAK_5_20_SNR | EB_WSE_WEAK_20_40_NE | EB_WSE_WEAK_20_40_SNR | FB_FRE_HIGH_ENERGY_RATIO | FB_FRE_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_HIGH_NE | FB_FRE_HIGH_SNR | FB_FRE_LOW_ENERGY_RATIO | FB_FRE_LOW_FREQUENCY_RANGE_HZ | FB_FRE_LOW_NE | FB_FRE_LOW_SNR | FB_FRE_MID_ENERGY_RATIO | FB_FRE_MID_FREQUENCY_RANGE_HZ | FB_FRE_MID_NE | FB_FRE_MID_SNR | FB_FRE_VERY_HIGH_ENERGY_RATIO | FB_FRE_VERY_HIGH_FREQUENCY_RANGE_HZ | FB_FRE_VERY_HIGH_NE | FB_FRE_VERY_HIGH_SNR | |
| |---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |
| | Raw (noisy) | - | 5.0008+-0.0009 | 29.6672+-0.0009 | 0.7412+-0.0000 | 0.027675+-0.000003 | 0.001274+-0.000000 | 0.034710+-0.000004 | 2.257791+-0.000581 | -6.4925+-0.0012 | 0.283060+-0.000027 | 10.9651+-0.0007 | 6.197356+-0.000997 | -15.2144+-0.0020 | 3.917280+-0.001631 | -11.2456+-0.0045 | 0.261746+-0.000000 | 93.2-135.68 | 0.426453+-0.000102 | 7.4242+-0.0022 | 0.045443+-0.000000 | 22.4-50.72 | 0.849846+-0.000121 | 1.4693+-0.0014 | 0.546771+-0.000000 | 50.72-93.2 | 0.293522+-0.000054 | 10.6508+-0.0017 | 0.013773+-0.000000 | 135.68-164 | 1.558689+-0.000412 | -3.7254+-0.0027 | |
| | UNet | 7.76 | 14.8942+-0.3700 | 39.5606+-0.3700 | 0.9680+-0.0025 | 0.007678+-0.000290 | 0.000126+-0.000010 | 0.010946+-0.000442 | 0.714249+-0.027722 | 3.1084+-0.3429 | 0.137881+-0.006947 | 17.3488+-0.4074 | 1.162586+-0.043836 | -0.9059+-0.2126 | 0.946346+-0.030802 | 0.7207+-0.2463 | 0.261746+-0.000000 | 93.2-135.68 | 0.201185+-0.008803 | 14.0032+-0.3651 | 0.045443+-0.000000 | 22.4-50.72 | 0.205482+-0.011952 | 13.8114+-0.4857 | 0.546771+-0.000000 | 50.72-93.2 | 0.123803+-0.004042 | 18.2594+-0.2550 | 0.013773+-0.000000 | 135.68-164 | 0.636248+-0.027683 | 4.0065+-0.3887 | |
| | ddpm | 33.30 | 14.3553+-0.0858 | 39.0217+-0.0858 | 0.9621+-0.0002 | 0.008738+-0.000091 | 0.000132+-0.000002 | 0.011341+-0.000104 | 1.054117+-0.024340 | 2.3810+-0.0318 | 0.122036+-0.001159 | 18.6040+-0.0559 | 2.833570+-0.097970 | -4.7729+-0.1410 | 1.776251+-0.054730 | -1.4268+-0.0888 | 0.261746+-0.000000 | 93.2-135.68 | 0.209589+-0.002885 | 14.0292+-0.0722 | 0.045443+-0.000000 | 22.4-50.72 | 0.233102+-0.004432 | 13.0278+-0.1433 | 0.546771+-0.000000 | 50.72-93.2 | 0.131609+-0.001525 | 17.8881+-0.0724 | 0.013773+-0.000000 | 135.68-164 | 0.696310+-0.013094 | 4.3042+-0.0642 | |
| | unet_L | 31.04 | 15.8185+-0.0527 | 40.4850+-0.0527 | 0.9729+-0.0003 | 0.006927+-0.000031 | 0.000103+-0.000001 | 0.009884+-0.000062 | 0.660273+-0.004102 | 3.7915+-0.0365 | 0.120375+-0.000898 | 18.4982+-0.0627 | 1.108190+-0.031093 | -0.5299+-0.1210 | 0.895929+-0.013935 | 1.1877+-0.0580 | 0.261746+-0.000000 | 93.2-135.68 | 0.183253+-0.001204 | 14.7863+-0.0551 | 0.045443+-0.000000 | 22.4-50.72 | 0.176294+-0.001233 | 15.1331+-0.0614 | 0.546771+-0.000000 | 50.72-93.2 | 0.115025+-0.001534 | 18.8685+-0.1149 | 0.013773+-0.000000 | 135.68-164 | 0.558383+-0.000925 | 5.1298+-0.0175 | |
| | SCRN | 0.43 | 17.0666+-0.0069 | 41.7330+-0.0069 | 0.9773+-0.0000 | 0.006135+-0.000014 | 0.000080+-0.000000 | 0.008664+-0.000011 | 0.597209+-0.001365 | 4.5752+-0.0118 | 0.097600+-0.000071 | 20.2588+-0.0087 | 1.016020+-0.004507 | 0.0086+-0.0122 | 0.823323+-0.002485 | 1.7824+-0.0094 | 0.261746+-0.000000 | 93.2-135.68 | 0.160988+-0.000158 | 15.8839+-0.0050 | 0.045443+-0.000000 | 22.4-50.72 | 0.147595+-0.000764 | 16.6539+-0.0470 | 0.546771+-0.000000 | 50.72-93.2 | 0.104533+-0.000191 | 19.6483+-0.0194 | 0.013773+-0.000000 | 135.68-164 | 0.470337+-0.000708 | 6.5986+-0.0088 | |
| | Attention UNet | 7.85 | 14.9159+-0.2220 | 39.5823+-0.2220 | 0.9679+-0.0014 | 0.007624+-0.000167 | 0.000124+-0.000005 | 0.010889+-0.000244 | 0.719303+-0.019091 | 3.0967+-0.1906 | 0.137268+-0.004106 | 17.4067+-0.2255 | 1.177993+-0.051667 | -0.8501+-0.2388 | 0.955511+-0.029984 | 0.7314+-0.1889 | 0.313958+-0.000000 | 93.2-135.68 | 0.199382+-0.005178 | 14.0859+-0.1926 | 0.055981+-0.000000 | 22.4-50.72 | 0.204836+-0.007038 | 13.8385+-0.2929 | 0.612267+-0.000000 | 50.72-93.2 | 0.125120+-0.002960 | 18.1853+-0.1691 | 0.017547+-0.000000 | 135.68-164 | 0.603594+-0.018403 | 4.4577+-0.2531 | |
| | DnCNN | - | 16.7555+-0.0116 | 41.4220+-0.0116 | 0.9758+-0.0000 | 0.006463+-0.000017 | 0.000085+-0.000000 | 0.008949+-0.000011 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | fbresnet | - | 16.0431+-0.0415 | 40.7096+-0.0415 | 0.9729+-0.0002 | 0.006877+-0.000045 | 0.000099+-0.000001 | 0.009657+-0.000045 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | ffcnn | - | 16.8487+-0.0150 | 41.5151+-0.0150 | 0.9773+-0.0001 | 0.006200+-0.000026 | 0.000082+-0.000000 | 0.008821+-0.000013 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
| | q_unet | 21.88 | 15.7674+-0.0369 | 40.4338+-0.0369 | 0.9729+-0.0001 | 0.006958+-0.000084 | 0.000104+-0.000000 | 0.009923+-0.000011 | 0.664895+-0.004956 | 3.7415+-0.0232 | 0.121137+-0.000344 | 18.4492+-0.0123 | 1.118569+-0.030170 | -0.5356+-0.1192 | 0.900699+-0.012578 | 1.1588+-0.0738 | 0.313958+-0.000000 | 93.2-135.68 | 0.184919+-0.001131 | 14.7162+-0.0380 | 0.055981+-0.000000 | 22.4-50.72 | 0.174458+-0.000909 | 15.2165+-0.0411 | 0.612267+-0.000000 | 50.72-93.2 | 0.115738+-0.000543 | 18.8179+-0.0170 | 0.017547+-0.000000 | 135.68-164 | 0.544606+-0.001930 | 5.3568+-0.0264 | |
| | ResUNet | 8.11 | 14.9234+-0.0476 | 39.5899+-0.0476 | 0.9694+-0.0005 | 0.007797+-0.000072 | 0.000125+-0.000001 | 0.010912+-0.000061 | 0.716673+-0.008124 | 3.1670+-0.0703 | 0.136956+-0.000509 | 17.3769+-0.0353 | 1.196153+-0.026646 | -0.9352+-0.1176 | 0.958101+-0.013175 | 0.7631+-0.0747 | 0.313958+-0.000000 | 93.2-135.68 | 0.199965+-0.000575 | 14.0362+-0.0273 | 0.055981+-0.000000 | 22.4-50.72 | 0.192186+-0.002288 | 14.3813+-0.1019 | 0.612267+-0.000000 | 50.72-93.2 | 0.121311+-0.000361 | 18.4151+-0.0235 | 0.017547+-0.000000 | 135.68-164 | 0.615606+-0.003820 | 4.2918+-0.0517 | |
| | unet_plusplus | - | 16.1603+-0.0714 | 40.8267+-0.0714 | 0.9741+-0.0005 | 0.006662+-0.000060 | 0.000095+-0.000001 | 0.009487+-0.000040 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | |
|
|
| <!-- AUTO_RESULTS_DATA_BEGIN |
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| 93.2 |
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| 164.0 |
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| "models": { |
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| "ddpm": { |
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| "eb_wse_weak_20_40_ne": { |
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| 135.68 |
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| 50.72 |
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| 93.2 |
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| "unet_L": { |
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| "eb_wse_medium_40_70_snr": { |
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| "eb_wse_weak_20_40_ne": { |
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| "std": 0.000106 |
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| "fbresnet": { |
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| "psnr": { |
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| "ddpm": { |
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| "std": 0.018537 |
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| "std": 0.025161 |
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| "std": 0.105392 |
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| 50.72 |
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| 93.2 |
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| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
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| "mse": { |
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| "psnr": { |
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| "cbdrdn": { |
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| "eb_wse_medium_40_70_snr": { |
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| "eb_wse_strong_70_100_ne": { |
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| "eb_wse_strong_70_100_snr": { |
| "mean": 16.019394, |
| "std": 0.530908 |
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| "eb_wse_very_weak_5_20_ne": { |
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| "std": 0.062357 |
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| "eb_wse_very_weak_5_20_snr": { |
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| "std": 0.347051 |
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| "eb_wse_weak_20_40_ne": { |
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| "std": 0.02489 |
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| "eb_wse_weak_20_40_snr": { |
| "mean": 0.031322, |
| "std": 0.150514 |
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| "fb_fre_high_energy_ratio": { |
| "mean": 0.313958, |
| "std": 0.0 |
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| "fb_fre_high_frequency_range_hz": [ |
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| 135.68 |
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| "fb_fre_high_ne": { |
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| "fb_fre_high_snr": { |
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| "fb_fre_low_energy_ratio": { |
| "mean": 0.055981, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
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| 50.72 |
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| "fb_fre_low_ne": { |
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| "std": 0.014684 |
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| "std": 0.593423 |
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| "fb_fre_mid_energy_ratio": { |
| "mean": 0.612267, |
| "std": 0.0 |
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| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
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| "fb_fre_mid_ne": { |
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| "std": 0.006907 |
| }, |
| "fb_fre_mid_snr": { |
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| "std": 0.372792 |
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| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.017547, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
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| "std": 0.04007 |
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| "mae": { |
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| "rmse": { |
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| "ssim": { |
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| "std": 0.003985 |
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| "unet_L": { |
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| "eb_wse_medium_40_70_snr": { |
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| "eb_wse_strong_70_100_ne": { |
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| "eb_wse_very_weak_5_20_ne": { |
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| "eb_wse_weak_20_40_ne": { |
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| 135.68 |
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| }, |
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| 50.72 |
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| "std": 0.226846 |
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| "std": 0.043808 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
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| "eb_wse_weak_20_40_ne": { |
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| "eb_wse_weak_20_40_snr": { |
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| "fb_fre_high_energy_ratio": { |
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| "std": 0.0 |
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| 135.68 |
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| "fb_fre_high_snr": { |
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| "fb_fre_mid_energy_ratio": { |
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| "std": 0.0 |
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| 93.2 |
| ], |
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| "std": 0.001785 |
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| "std": 0.136623 |
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| "fb_fre_very_high_energy_ratio": { |
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| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
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| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
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| "fb_fre_very_high_snr": { |
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| "std": 0.182935 |
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| "mae": { |
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| "std": 7.5e-05 |
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| "mse": { |
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| "rmse": { |
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| "std": 0.000167 |
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| "snr": { |
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| "std": 0.150004 |
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| "ssim": { |
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| "std": 0.000873 |
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| "dncnn": { |
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| "std": 4e-05 |
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| "mse": { |
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| "std": 1e-06 |
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| "psnr": { |
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| "std": 0.049195 |
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| "rmse": { |
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| "std": 4.1e-05 |
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| "snr": { |
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| "std": 0.049164 |
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| "ssim": { |
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| "std": 0.000249 |
| } |
| }, |
| "res_unet": { |
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| "std": 0.006742 |
| }, |
| "eb_wse_medium_40_70_snr": { |
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| "std": 0.066304 |
| }, |
| "eb_wse_strong_70_100_ne": { |
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| "eb_wse_strong_70_100_snr": { |
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| "std": 0.03749 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
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| "std": 0.021451 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
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| "std": 0.101287 |
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| "eb_wse_weak_20_40_ne": { |
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| "std": 0.010687 |
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| "eb_wse_weak_20_40_snr": { |
| "mean": 0.782715, |
| "std": 0.06254 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.313958, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
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| 135.68 |
| ], |
| "fb_fre_high_ne": { |
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| "std": 0.000695 |
| }, |
| "fb_fre_high_snr": { |
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| "std": 0.031199 |
| }, |
| "fb_fre_low_energy_ratio": { |
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| "std": 0.0 |
| }, |
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| 50.72 |
| ], |
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| }, |
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| "std": 0.105451 |
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| "fb_fre_mid_energy_ratio": { |
| "mean": 0.612267, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
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| "std": 0.000425 |
| }, |
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| "mean": 18.412671, |
| "std": 0.026981 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
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| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
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| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
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| "std": 0.002927 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 4.31517, |
| "std": 0.047079 |
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| "mae": { |
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| "std": 7.2e-05 |
| }, |
| "mse": { |
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| "std": 1e-06 |
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| "psnr": { |
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| "std": 0.049541 |
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| "rmse": { |
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| "std": 6.2e-05 |
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| "snr": { |
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| "std": 0.049583 |
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| "ssim": { |
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| "std": 0.000525 |
| } |
| }, |
| "atten_unet": { |
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| "std": 0.019492 |
| }, |
| "eb_wse_medium_40_70_snr": { |
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| "std": 0.201117 |
| }, |
| "eb_wse_strong_70_100_ne": { |
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| "std": 0.004234 |
| }, |
| "eb_wse_strong_70_100_snr": { |
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| "std": 0.238956 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
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| "std": 0.052686 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -0.816266, |
| "std": 0.242681 |
| }, |
| "eb_wse_weak_20_40_ne": { |
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| "std": 0.029417 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 0.743522, |
| "std": 0.201517 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.313958, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
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| 135.68 |
| ], |
| "fb_fre_high_ne": { |
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| "std": 0.005196 |
| }, |
| "fb_fre_high_snr": { |
| "mean": 14.060391, |
| "std": 0.199171 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.055981, |
| "std": 0.0 |
| }, |
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| 22.4, |
| 50.72 |
| ], |
| "fb_fre_low_ne": { |
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| "std": 0.006843 |
| }, |
| "fb_fre_low_snr": { |
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| "std": 0.286675 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.612267, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
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| "std": 0.003045 |
| }, |
| "fb_fre_mid_snr": { |
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| "std": 0.180962 |
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| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.017547, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
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| "std": 0.019445 |
| }, |
| "fb_fre_very_high_snr": { |
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| "std": 0.268462 |
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| "std": 0.000174 |
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| "mse": { |
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| "std": 6e-06 |
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| "psnr": { |
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| "std": 0.228716 |
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| "rmse": { |
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| "std": 0.000255 |
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| "snr": { |
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| "ssim": { |
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| "std": 0.001352 |
| } |
| }, |
| "unet_plusplus": { |
| "mae": { |
| "mean": 0.006638, |
| "std": 5.6e-05 |
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| "mse": { |
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| "std": 0.0 |
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| "psnr": { |
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| "rmse": { |
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| "std": 3.1e-05 |
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| "snr": { |
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| "std": 0.054417 |
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| "ssim": { |
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| "std": 0.000309 |
| } |
| }, |
| "ffcnn": { |
| "mae": { |
| "mean": 0.006203, |
| "std": 1.3e-05 |
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| "mse": { |
| "mean": 8.3e-05, |
| "std": 0.0 |
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| "psnr": { |
| "mean": 41.499967, |
| "std": 0.015969 |
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| "rmse": { |
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| "std": 1.1e-05 |
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| "snr": { |
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| "std": 0.015969 |
| }, |
| "ssim": { |
| "mean": 0.977267, |
| "std": 4.7e-05 |
| } |
| }, |
| "SCRN": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 0.597121, |
| "std": 0.00272 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 4.569923, |
| "std": 0.027267 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.097873, |
| "std": 5e-05 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 20.235199, |
| "std": 0.008665 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 1.009696, |
| "std": 0.008051 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": 0.049737, |
| "std": 0.03238 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 0.821374, |
| "std": 0.004438 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 1.789523, |
| "std": 0.024592 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.261746, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 93.2, |
| 135.68 |
| ], |
| "fb_fre_high_ne": { |
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| "std": 0.000307 |
| }, |
| "fb_fre_high_snr": { |
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| "std": 0.016071 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.045443, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 22.4, |
| 50.72 |
| ], |
| "fb_fre_low_ne": { |
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| "std": 0.000305 |
| }, |
| "fb_fre_low_snr": { |
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| "std": 0.021304 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.546771, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.104686, |
| "std": 0.000163 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 19.636664, |
| "std": 0.016891 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.013773, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
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| "std": 0.00161 |
| }, |
| "fb_fre_very_high_snr": { |
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| "std": 0.026513 |
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| "mae": { |
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| "std": 1.6e-05 |
| }, |
| "mse": { |
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| "std": 0.0 |
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| "psnr": { |
| "mean": 41.721533, |
| "std": 0.012302 |
| }, |
| "rmse": { |
| "mean": 0.008675, |
| "std": 1.2e-05 |
| }, |
| "snr": { |
| "mean": 17.0551, |
| "std": 0.012283 |
| }, |
| "ssim": { |
| "mean": 0.977333, |
| "std": 9.4e-05 |
| } |
| }, |
| "fbresnet": { |
| "mae": { |
| "mean": 0.006889, |
| "std": 1.9e-05 |
| }, |
| "mse": { |
| "mean": 9.9e-05, |
| "std": 1e-06 |
| }, |
| "psnr": { |
| "mean": 40.690267, |
| "std": 0.035896 |
| }, |
| "rmse": { |
| "mean": 0.009679, |
| "std": 3.4e-05 |
| }, |
| "snr": { |
| "mean": 16.023833, |
| "std": 0.035863 |
| }, |
| "ssim": { |
| "mean": 0.972833, |
| "std": 0.000236 |
| } |
| }, |
| "ddpm": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 1.056677, |
| "std": 0.039264 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 2.354287, |
| "std": 0.167491 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.122586, |
| "std": 0.002645 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 18.563863, |
| "std": 0.139006 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 2.856104, |
| "std": 0.169225 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -4.885888, |
| "std": 0.374213 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 1.785473, |
| "std": 0.088003 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": -1.495197, |
| "std": 0.27216 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.261746, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 93.2, |
| 135.68 |
| ], |
| "fb_fre_high_ne": { |
| "mean": 0.210138, |
| "std": 0.005565 |
| }, |
| "fb_fre_high_snr": { |
| "mean": 14.000558, |
| "std": 0.175995 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.045443, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 22.4, |
| 50.72 |
| ], |
| "fb_fre_low_ne": { |
| "mean": 0.233449, |
| "std": 0.008681 |
| }, |
| "fb_fre_low_snr": { |
| "mean": 13.01016, |
| "std": 0.287871 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.546771, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.131869, |
| "std": 0.0027 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 17.868241, |
| "std": 0.142826 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.013773, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.699858, |
| "std": 0.023049 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 4.256153, |
| "std": 0.170547 |
| }, |
| "mae": { |
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| "std": 0.000244 |
| }, |
| "mse": { |
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| "std": 7e-06 |
| }, |
| "psnr": { |
| "mean": 38.977367, |
| "std": 0.233067 |
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| "rmse": { |
| "mean": 0.011406, |
| "std": 0.000293 |
| }, |
| "snr": { |
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| "std": 0.233114 |
| }, |
| "ssim": { |
| "mean": 0.9607, |
| "std": 0.003121 |
| } |
| }, |
| "cbdrdn": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 0.641893, |
| "std": 0.029979 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 3.993264, |
| "std": 0.367617 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.105119, |
| "std": 0.007073 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 19.646053, |
| "std": 0.527272 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 1.064784, |
| "std": 0.039411 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -0.272648, |
| "std": 0.214598 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 0.86799, |
| "std": 0.024057 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 1.399221, |
| "std": 0.173087 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.313958, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 93.2, |
| 135.68 |
| ], |
| "fb_fre_high_ne": { |
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| "std": 0.008958 |
| }, |
| "fb_fre_high_snr": { |
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| "std": 0.426877 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.055981, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 22.4, |
| 50.72 |
| ], |
| "fb_fre_low_ne": { |
| "mean": 0.159543, |
| "std": 0.011129 |
| }, |
| "fb_fre_low_snr": { |
| "mean": 15.9988, |
| "std": 0.576151 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.612267, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.112184, |
| "std": 0.005648 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 19.054077, |
| "std": 0.399762 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.017547, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.490332, |
| "std": 0.033179 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 6.259377, |
| "std": 0.561981 |
| }, |
| "mae": { |
| "mean": 0.006755, |
| "std": 0.00042 |
| }, |
| "mse": { |
| "mean": 9.2e-05, |
| "std": 9e-06 |
| }, |
| "psnr": { |
| "mean": 41.125133, |
| "std": 0.469713 |
| }, |
| "rmse": { |
| "mean": 0.00928, |
| "std": 0.000453 |
| }, |
| "snr": { |
| "mean": 16.458667, |
| "std": 0.469666 |
| }, |
| "ssim": { |
| "mean": 0.9738, |
| "std": 0.002406 |
| } |
| }, |
| "unet_L": { |
| "eb_wse_medium_40_70_ne": { |
| "mean": 0.657661, |
| "std": 0.003585 |
| }, |
| "eb_wse_medium_40_70_snr": { |
| "mean": 3.791945, |
| "std": 0.055172 |
| }, |
| "eb_wse_strong_70_100_ne": { |
| "mean": 0.119565, |
| "std": 0.001454 |
| }, |
| "eb_wse_strong_70_100_snr": { |
| "mean": 18.546761, |
| "std": 0.103899 |
| }, |
| "eb_wse_very_weak_5_20_ne": { |
| "mean": 1.095432, |
| "std": 0.015124 |
| }, |
| "eb_wse_very_weak_5_20_snr": { |
| "mean": -0.496318, |
| "std": 0.051614 |
| }, |
| "eb_wse_weak_20_40_ne": { |
| "mean": 0.88948, |
| "std": 0.006917 |
| }, |
| "eb_wse_weak_20_40_snr": { |
| "mean": 1.205066, |
| "std": 0.025467 |
| }, |
| "fb_fre_high_energy_ratio": { |
| "mean": 0.261746, |
| "std": 0.0 |
| }, |
| "fb_fre_high_frequency_range_hz": [ |
| 93.2, |
| 135.68 |
| ], |
| "fb_fre_high_ne": { |
| "mean": 0.18334, |
| "std": 0.001258 |
| }, |
| "fb_fre_high_snr": { |
| "mean": 14.774071, |
| "std": 0.057648 |
| }, |
| "fb_fre_low_energy_ratio": { |
| "mean": 0.045443, |
| "std": 0.0 |
| }, |
| "fb_fre_low_frequency_range_hz": [ |
| 22.4, |
| 50.72 |
| ], |
| "fb_fre_low_ne": { |
| "mean": 0.174386, |
| "std": 0.002595 |
| }, |
| "fb_fre_low_snr": { |
| "mean": 15.223469, |
| "std": 0.128151 |
| }, |
| "fb_fre_mid_energy_ratio": { |
| "mean": 0.546771, |
| "std": 0.0 |
| }, |
| "fb_fre_mid_frequency_range_hz": [ |
| 50.72, |
| 93.2 |
| ], |
| "fb_fre_mid_ne": { |
| "mean": 0.114728, |
| "std": 0.001854 |
| }, |
| "fb_fre_mid_snr": { |
| "mean": 18.884683, |
| "std": 0.137712 |
| }, |
| "fb_fre_very_high_energy_ratio": { |
| "mean": 0.013773, |
| "std": 0.0 |
| }, |
| "fb_fre_very_high_frequency_range_hz": [ |
| 135.68, |
| 164.0 |
| ], |
| "fb_fre_very_high_ne": { |
| "mean": 0.555501, |
| "std": 0.002575 |
| }, |
| "fb_fre_very_high_snr": { |
| "mean": 5.176272, |
| "std": 0.038653 |
| }, |
| "mae": { |
| "mean": 0.006915, |
| "std": 5.2e-05 |
| }, |
| "mse": { |
| "mean": 0.000103, |
| "std": 2e-06 |
| }, |
| "psnr": { |
| "mean": 40.515, |
| "std": 0.070545 |
| }, |
| "rmse": { |
| "mean": 0.009869, |
| "std": 8.3e-05 |
| }, |
| "snr": { |
| "mean": 15.848533, |
| "std": 0.070571 |
| }, |
| "ssim": { |
| "mean": 0.972967, |
| "std": 0.000634 |
| } |
| } |
| } |
| } |
| } |
| }, |
| "num_params": { |
| "unet": 7760000, |
| "ddpm": 33300000, |
| "unet_L": 31040000, |
| "SCRN": 430000, |
| "cbdrdn": 1490000, |
| "q_unet": 21880000, |
| "atten_unet": 7850000, |
| "res_unet": 8110000 |
| } |
| } |
| AUTO_RESULTS_DATA_END --> |
| <!-- AUTO_RESULTS_END --> |
