[TGRS 2022]The code in this toolbox implements the "A Complementary Spectral-Spatial Method for Hyperspectral Image Classification".
Please kindly cite the papers if this code is useful and helpful for your research.
L. Shi, C. Li, T. Li and Y. Peng, "A Complementary Spectral-Spatial Method for Hyperspectral Image Classification," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022, Art no. 5531017, doi: 10.1109/TGRS.2022.3180935.
@article{shi2022complementary,
title={A Complementary Spectral-Spatial Method for Hyperspectral Image Classification},
author={Shi, Lulu and Li, Chunchao and Li, Teng and Peng, Yuanxi},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={60},
pages={1--17},
year={2022},
publisher={IEEE}
}The data were generated by Matlab R2020b or higher versions.
All experimental datasets can be found on the following two websites. Thanks again to the datasets providers.
https://rslab.ut.ac.ir/data
https://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes#Pavia_University_scene
The original code is based on Pavia University dataset.
- Download the dataset and put it in the code file.
- Modify the corresponding parameters in the "Prepare image" module.
- Modify the visual color options in the "Visualization" module according to the corresponding dataset.
- Run demo.m
Lulu Shi: nudtersll@126.com
Lulu Shi is currently studying for a master's degree in the college of Computer Science, National University of Defense Technology.