/Hyperspectral-TargetDet-SSAD

Primary LanguagePythonMIT LicenseMIT

A Semantic Transferred Priori for Hyperspectral Target Detection with Spatial-Spectral Association [IEEE TGRS 2023]

This is the official repository of the paper ''A Semantic Transferred Priori for Hyperspectral Target Detection with Spatial-Spectral Association''.

Jie Lei, Simin Xu, Weiying Xie∗, Jiaqing Zhang, Yunsong Li, and Qian Du

Train.

During the training phase, process the dataset according to ./dataset and run:

python train.py

Test.

During the testing phase, run:

python test.py

Matlab Code.

Run the ./matlab_code_Make_d/maked.m to generate a precise customized target spectrum for subsequent spectral detection. The corrected spectrum has been experimentally verified to significantly enhance the detection accuracy across various methods.

Citation.

If you find this project useful for your research, please use the following BibTeX entry.

@article{lei2023semantic,
  title={A Semantic Transferred Priori for Hyperspectral Target Detection With Spatial--Spectral Association},
  author={Lei, Jie and Xu, Simin and Xie, Weiying and Zhang, Jiaqing and Li, Yunsong and Du, Qian},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  volume={61},
  pages={1--14},
  year={2023},
  publisher={IEEE}
}