This is the code of paper named "Learnable Background Endmember with Subspace Representation for Hyperspectral Anomaly Detection".
For more information of this project, please refer to our paper:
T. Guo, L. He, F. Luo, X. Gong, L. Zhang and X. Gao, "Learnable Background Endmember With Subspace Representation for Hyperspectral Anomaly Detection," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-13, 2024, Art no. 5501513, doi: 10.1109/TGRS.2023.3341245.
matlab R2020a
If these codes and dataset are helpful for you, please cite this paper:
@ARTICLE{10352161,
author={Guo, Tan and He, Long and Luo, Fulin and Gong, Xiuwen and Zhang, Lei and Gao, Xinbo},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={Learnable Background Endmember With Subspace Representation for Hyperspectral Anomaly Detection},
year={2024},
volume={62},
number={},
pages={1-13},
doi={10.1109/TGRS.2023.3341245}}
Code and datasets are released for non-commercial and research purposes only. For commercial purposes, please contact the authors.