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An Iterative Regularization Method for Total Variation-Based Image Restoration
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An Iterative Regularization Method for Total Variation-Based Image Restoration
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Journal Article
An Iterative Regularization Method for Total Variation-Based Image Restoration
2005
Overview
We introduce a new iterative regularization procedure for inverse problems based on the use of Bregman distances, with particular focus on problems arising in image processing. We are motivated by the problem of restoring noisy and blurry images via variational methods by using total variation regularization. We obtain rigorous convergence results and effective stopping criteria for the general procedure. The numerical results for denoising appear to give significant improvement over standard models, and preliminary results for deblurring/denoising are very encouraging.
Publisher
Society for Industrial and Applied Mathematics
Subject
