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Conference Papers Year : 2009

A proximal method for inverse problems in image processing

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Abstract

In this paper, we present a new algorithm to solve some inverse problems coming from the field of image processing. The models we study consist in minimizing a regularizing, convex criterion under a convex and compact set. The main idea of our scheme consists in solving the underlying variational inequality with a proximal method rather than the initial convex problem. Using recent results of A. Nemirovski [13], we show that the scheme converges at least as O(1/k) (where k is the iteration counter). This is in some sense an optimal rate of convergence. Finally, we compare this approach to some others on a problem of image cartoon+texture decomposition.
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Dates and versions

inria-00417712 , version 1 (16-09-2009)

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  • HAL Id : inria-00417712 , version 1

Cite

Pierre Weiss, Laure Blanc-Féraud. A proximal method for inverse problems in image processing. EUSIPCO, Aug 2009, Glasgow, United Kingdom. ⟨inria-00417712⟩
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