Using Geometry and Iterated Refinement for Inverse Problems (1): Total Variation Based Image Restoration
نویسندگان
چکیده
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, specifically by using the BV seminorm. Although our procedure applies in quite general situations it was obtained by geometric considerations (first discussed in [23]) associated with the Rudin-OsherFatemi procedure developed in [29] for image restoration. We obtain rigorous convergence results, and effective stopping criteria for the general procedure. The numerical results for denoising appear to be state-of-the-art and preliminary results for deblurring/denoising are very encouraging.
منابع مشابه
Corc Technical Report Tr-2004-03 Using Geometry and Iterated Refinement for Inverse Problems (1): Total Variation Based Image Restoration
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, specifically by using the BV seminorm. Although our procedure applies in quite general situations it was obtained by geometric...
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