Skip to content

Latest commit

 

History

History
46 lines (26 loc) · 1.9 KB

README.md

File metadata and controls

46 lines (26 loc) · 1.9 KB
Raw

HSID-CNN

Matlab demo code for Hyperspectral Image Denoising Employing a Spatial–Spectral Deep Residual Convolutional Neural Network(HSID-CNN), IEEE TGRS, 2019.

By Qiang Zhang (whuqzhang@gmail.com)
Wuhan University, China.

If you use/adapt our code in your work (either as a stand-alone tool or as a component of any algorithm), please cite our paper.

Q. Yuan, Q. Zhang, J. Li, H. Shen, and L. Zhang, "Hyperspectral Image Denoising Employing a Spatial–Spectral Deep Residual Convolutional Neural Network," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 2, pp. 1205-1218, 2019.

  @ARTICLE{yuan2019,
  author={Q. {Yuan} and Q. {Zhang} and J. {Li} and H. {Shen} and L. {Zhang}}, 
  journal={IEEE Trans. Geosci. Remote Sens.}, 
  title={Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network}, 
  year={2019}, 
  volume={57}, 
  number={2}, 
  pages={1205-1218},  
  month={Feb.},}

This code is for academic purpose only. Not for commercial/industrial activities.

NOTE:

This Matlab version is a re-implementation with HSID-CNN (https://ieeexplore.ieee.org/document/8454887, IEEE TGRS, 2019), and is for the ease of understanding the algorithm. This code is not optimized, and the speed is not representative. The result can be slightly different from the paper due to transferring across platforms.

Enviroment:

 Window 7, Cuda 7.5, Caffe framework (**Necessary, GPU mode better**), Matlab R2014b. 
 Place set this folder into "($Caffe_Dir)/examples/"

Others:

 If you need more models, please contact me. (whuqzhang@gmail.com)