Minghua Wang; Danfeng Hong; Bing Zhang; Longfei Ren; Jing Yao; Jocelyn Chanussot
Please kindly cite the papers if this code is useful and helpful for your research.
M. Wang, D. Hong, B. Zhang, L. Ren, J. Yao and J. Chanussot, "Learning Double Subspace Representation for Joint Hyperspectral Anomaly Detection and Noise Removal," in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-17, 2023, Art no. 5507517, doi: 10.1109/TGRS.2023.3261964. @ARTICLE{10081488, author={Wang, Minghua and Hong, Danfeng and Zhang, Bing and Ren, Longfei and Yao, Jing and Chanussot, Jocelyn}, journal={IEEE Transactions on Geoscience and Remote Sensing}, title={Learning Double Subspace Representation for Joint Hyperspectral Anomaly Detection and Noise Removal}, year={2023}, volume={61}, number={}, pages={1-17}, doi={10.1109/TGRS.2023.3261964}} System-specific notes The code was tested in Matlab R2018b or higher versions on Windows 10 machines.
Directly run demo_San_Diego.m to reproduce the results on the Sandiego_new.mat, which exists in the aforementioned paper. Note that the data can be included in the file.
If you want to run the code in your own data, you can accordingly change the input (e.g., data) and tune the parameters (important).
If you encounter the bugs while using this code, please do not hesitate to contact us.
This work was supported in part by the National Natural Science Foundation of China under Grant 62201552 and China Postdoctoral Science Foundation; in part by the MIAI@Grenoble Alpes under Grant ANR-19-P3IA-0003
Copyright (C) 2023 Minghua Wang This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program.
Minghua Wang (minghuawang1993@163.com) the Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China