TV-L1 Image Denoising Algorithm

Easy to read function for TV-L1 image denoising

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Updated 15 Jun 2017

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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 (2023). 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
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.