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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: πŸ‘‰ GitHub: MWan-deeplearner/BTC-Net-V2


πŸ“Œ 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.

πŸ“‚ 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:

.
β”œβ”€β”€ README.md                           # This Dataset Card
└── aviris_mat_chunk_01.zip            # Sub-dataset chunk 01 (Contains files 1-100)
β”œβ”€β”€ 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)
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