TV-L1 Image Denoising Algorithm

Easy to read function for TV-L1 image denoising
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Updated Thu, 15 Jun 2017 10:39:10 +0000

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Image denoising using the TV-L1 model optimized with a primal-dual algorithm.
The function minimizes the following denoising model wrt I:
sum(sqrt(Ix^2 + Iy^2)) + lambda*||I - g||
where I is the denoised image, Ix, Iy its gradient, g is the observed image and lambda
is the regularization coefficient. Smaller values for lambda result in more aggressive
denoising. For more details, see
* A. Mordvintsev: ROF and TV-L1 denoising with Primal-Dual algorithm,
http://znah.net/rof-and-tv-l1-denoising-with-primal-dual-algorithm.html
also archived as http://www.webcitation.org/6rEjLnF1F
* Chambolle et al. An introduction to Total Variation for Image Analysis, 2009. <hal-00437581>
https://hal.archives-ouvertes.fr/hal-00437581/document

Cite As

Manolis Lourakis (2024). TV-L1 Image Denoising Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/57604-tv-l1-image-denoising-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2013a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Denoising and Compression in Help Center and MATLAB Answers
Acknowledgements

Inspired by: ROF Denoising Algorithm

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Version Published Release Notes
1.0.0.0

Updated description.
Added hint about lambda.
Added archived tutorial page.