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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 (2026). TV-L1 Image Denoising Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/57604-tv-l1-image-denoising-algorithm), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: ROF Denoising Algorithm
General Information
- Version 1.0.0.0 (62.4 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 | Updated description.
|
