| --- |
| license: mit |
| task_categories: |
| - image-to-image |
| - other |
| tags: |
| - hyperspectral-imaging |
| - hsi-compression |
| - image-compression |
| - image-reconstruction |
| - deep-learning |
| - wireless-communications |
| pretty_name: BTC-Net V2 Dataset |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # BTC-Net V2: Spatial-Priority Hierarchical Reconstruction for Hyperspectral Image Compression |
|
|
| This repository contains the officially released dataset for **BTC-Net V2**. |
|
|
| For the complete implementation, network architectures, and pre-trained models, please visit our official GitHub repository: |
| 👉 **[GitHub: MWan-deeplearner/BTC-Net-V2](https://github.com/MWan-deeplearner/BTC-Net-V2)** |
|
|
| --- |
|
|
| ## 📌 Dataset Overview |
|
|
| This dataset consists of processed Hyperspectral Image (HSI) data (specifically from the AVIRIS sensor), structured and chunked to facilitate deep learning-based image compression and hierarchical wireless transmission research. |
|
|
| * **Data Format:** MATLAB `.mat` files packed into sequential `.zip` chunks. |
| * **Total Samples:** 1,195 processed HSI patches/sub-volumes. |
| * **Core Application:** Spatial-priority hierarchical reconstruction, HSI compression, deep learning. |
|
|
| --- |
|
|
| ## 📂 Repository Structure & Naming Convention |
|
|
| To prevent download interruptions caused by network fluctuations, the 1,195 `.mat` files are distributed evenly into **12 independent zip archives** (approx. 100 files per chunk). |
|
|
| The repository is structured as follows: |
|
|
| ```text |
| . |
| ├── README.md # This Dataset Card |
| └── aviris_mat_chunk_01.zip # Sub-dataset chunk 01 (Contains files 1-100) |
| ├── aviris_mat_chunk_02.zip # Sub-dataset chunk 02 (Contains files 101-200) |
| ... |
| └── aviris_mat_chunk_12.zip # Sub-dataset chunk 12 (Contains remaining files) |
