This is the code of paper named "A Spectral-Spatial Fusion Anomaly Detection Method for Hyperspectral Imagery".

For more information of this project, please refer to our paper:

Zengfu Hou, Siyuan Cheng and Ting Hu. A Spectral-Spatial Fusion Anomaly Detection Method for Hyperspectral Imagery [J]. arXiv:2202.11889.

matlab R2018a

If these codes and dataset are helpful for you, please cite this paper:

BibTex Format:

@article{hou2022spectral,
  title={A spectral-spatial fusion anomaly detection method for hyperspectral imagery},
  author={Hou, Zengfu and Cheng, Siyuan and Hu, Ting},
  journal={arXiv preprint arXiv:2202.11889},
  year={2022}
}

Plain Text Format:

Z. Hou, S. Chen, T. Hu. A spectral-spatial fusion anomaly detection method for hyperspectral imagery. arXiv preprint arXiv:2202.11889, 2022 Feb 24.

[1] Jun Liu, Zengfu Hou, Wei Li, Ran Tao, Danilo Orlando and Hongbin Li. Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery [J]. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2021.3071026. [Second author]

[2] Zengfu Hou, Wei Li, Ran Tao, Pengge Ma, and Weihua Shi. Collaborative Representation with Background Purification and Saliency Weight for Hyperspectral Anomaly Detection [J]. SCIENCE CHINA Information Sciences.2022 Jan, 65(1):1-12. doi: https://doi.org/10.1007/s11432-020-2915-2.

[3] Kun Tan, Zengfu Hou, Fuyu Wu,Qian Du, and Yu Chen. Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation [J]. Remote Sensing 2019, 11(11): 1318. [Co-first author]

[4] Kun Tan, Zengfu Hou, Dongelei Ma, Yu Chen, and Qian Du. Anomaly detection in hyperspectral imagery based on low-rank representation incorporating a spatial constraint [J]. Remote Sensing, 2019, 11(13): 1578. [Co-first author]

[5] Zengfu Hou, Wei Li, Lianru Gao, Bing Zhang, Pengge Ma, and Junlin Sun. A BACKGROUND REFINEMENT COLLABORATIVE REPRESENTATION METHOD WITH SALIENCY WEIGHT FOR HYPERSPECTRAL ANOMALY DETECTION [C]. International Geoscience and Remote Sensing, 2020. [Oral]

[6] Zengfu Hou, Yu Chen, Kun Tan, and Peijun Du. NOVEL HYPERSPECTRAL ANOMALY DETECTION METHODS BASED ON UNSUPERVISED NEAREST REGULARIZED SUBSPACE [C]. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2018, 42(3)

[7] Zengfu Hou, Kun Tan, Yu Chen, and Peijun Du. AN IMPROVED UNSUPERVISED NEAREST REGULARIZED SUBSPACE METHOD FOR HYPERSPECTRAL ANOMALY DETECTION [C]. International Conference on Advanced Remote Sensing, 2018.

1.Github Website: https://zephyrhours.github.io/

2.Chinese CSDN Blog: https://blog.csdn.net/NBDwo

If you have any other questions, you can send it to my email (See Github Website). I will get back to you as soon as possible!