Eigen-CNN: A fast hyperspectral image denoising network

Version 1.0.1 (2.02 MB) by Lina Zhuang
Eigen-CNN is a Eigenimages Plus Eigennoise Level Maps Guided Network for Hyperspectral Image Denoising developed in Matlab
32 Downloads
Updated 12 Sep 2024
%% The code and data herein distributed reproduces the results published in
% the paper
%
% Lina Zhuang, Michael K. Ng, Lianru Gao, and Zhicheng Wang,
% "Eigen-CNN: Eigenimages Plus Eigennoise Level Maps Guided Network for
% Hyperspectral Image Denoising,"
% IEEE Transactions on Geoscience and Remote Sensing (2024).
%
% URL: https://ieeexplore.ieee.org/abstract/document/10475370
%
%% Notes:
%
% 1) Package instalation: unzip the files to a directory and run the
% script of "main_runEigenCNN.m", which reproduce the
% results of Eigen-CNN reported in above paper.
%
%
% 2) MatConvNet toolbox must be installed before running this demo.
% MatConvNet is an implementation of Convolutional Neural Networks
% (CNNs) for MATLAB. The MatConvNet package is available at the
% matconvnet web page:
% https://github.com/vlfeat/matconvnet?tab=readme-ov-file
%
%
% 3) EigenCNN.m FastHyIn.m script implents the respective algorithm.
%
%% ACKNOWLEDGMENTS
%
% The authors acknowledge the following individuals and organisations:
%
%
% - Prof. Paolo Gamba from Pavia university,
% for making the Pavia Centre data set available to the community.
%
% - Prof. David Landgrebe and Larry Biehl from Purdue University,
% for making the Washington DC Mall data set available to the community.
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Author: Lina Zhuang, Sep. 2024
%

Cite As

Zhuang, L., Ng, M. K., Gao, L., & Wang, Z. (2024). Eigen-CNN: Eigenimages Plus Eigennoise Level Maps Guided Network for Hyperspectral Image Denoising. IEEE Transactions on Geoscience and Remote Sensing.

MATLAB Release Compatibility
Created with R2022a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.1

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1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.