The implement of the paper "A Semi-Supervised Multi-Scale Convolutional Sparse Coding-Guided Deep Interpretable Network for Hyperspectral Image Change Detection" (IEEE Transactions on Geoscience and Remote Sensing 2024)
- Ubuntu 20.04 cuda 11.4
- Python 3.8 Pytorch 1.12.1
The ./model/MSCSC.py include main model structure.
Please run demo.py for training and testing.
If you find this code helpful, please kindly cite:
@ARTICLE{10680161,
author={Qu, Jiahui and Yang, Peicheng and Dong, Wenqian and Zhang, Xiaohan and Li, Yunsong},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={A Semi-Supervised Multiscale Convolutional Sparse Coding-Guided Deep Interpretable Network for Hyperspectral Image Change Detection},
year={2024},
volume={62},
number={},
pages={1-14},
keywords={Feature extraction;Hyperspectral imaging;Training;Convolutional codes;Encoding;Filters;Supervised learning;Change detection (CD);deep interpretable network;hyperspectral image (HSI);multiscale convolutional sparse coding (MSCSC);semi-supervised learning},
doi={10.1109/TGRS.2024.3460105}}