Awesome

The code is for the work:

@article{jiang2019hyperspectral,
  title={Hyperspectral Image Classification in the Presence of Noisy Labels},
  author={Jiang, Junjun and Ma, Jiayi and Wang, Zheng and Chen, Chen and Liu, Xianming},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  volume={57},
  number={2},
  pages={851--865},
  year={2019}
}

@article{jiang2020learning,
 author={J. {Jiang} and J. {Ma} and X. {Liu}}, 
 journal={IEEE Transactions on Neural Networks and Learning Systems}, 
 title={Multilayer Spectral-Spatial Graphs for Label Noisy Robust Hyperspectral Image Classification}, 
 year={2020}, 
 volume={}, 
 number={}, 
 DOI={10.1109/TNNLS.2020.3029523},}

To generate the file of *_randp.mat for other database, you can use the randpTest.m to generate.

If you need another two datasets (PaviaU and Salinas), please feel free to contact me. Or you can download them from http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes

PaviaU: http://www.ehu.eus/ccwintco/uploads/e/ee/PaviaU.mat, http://www.ehu.eus/ccwintco/uploads/5/50/PaviaU_gt.mat

Salinas: http://www.ehu.eus/ccwintco/uploads/a/a3/Salinas_corrected.mat, http://www.ehu.eus/ccwintco/uploads/f/fa/Salinas_gt.mat