Impulse denoising
This code demonstrates impulse noise reduction from hyperspectral images.
It solves following optimization problem :
min_X || Y-X||_1 + lambda ||Dh*X||_1 + lamdba ||Dv*X||_1 + mu ||X||_*
X: Hyperspectral image
Y: Compressive measurements
Dh, Dv: Horizontal and vertical finite difference operators
||X||_* : Nuclear norm of matrix X
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How to Run this code :
Just run the demoDenoising.m file. It takes around 15 seconds to show the output on 160x160x64 hyperspectral image.
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File Description :
demoDenoising.m : Simply run this file to see how the code works.
funDenoising.m : It is the main function which solves above problem using split-Bregman technique.
HyperSpectralPatch.mat : This is the portion of Washington DC mall image downloaded from here:
link: https://engineering.purdue.edu/%7ebiehl/MultiSpec/hyperspectral.html
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Contact Information:
This code is released just to promote reproducible research and is not very robust.
If you face difficulty in running this code then please feel free to contact us.
Hemant Kumar Aggarwal( jnu.hemant@gmail.com )
Snigdha Tariyal (snigdha1491@iiitd.ac.in)
Cite As
Hemant Kumar Aggarwal (2024). Impulse denoising (https://www.mathworks.com/matlabcentral/fileexchange/48969-impulse-denoising), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Computer Vision Toolbox > Point Cloud Processing > Display Point Clouds >
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Version | Published | Release Notes | |
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1.0.0.0 |