2020
DOI: 10.48550/arxiv.2002.09180
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A symmetric alternating minimization algorithm for total variation minimization

Abstract: In this paper, we propose a novel symmetric alternating minimization algorithm to solve a broad class of total variation (TV) regularization problems. Unlike the usual z k → x k Gauss-Seidel cycle, the proposed algorithm performs the specialThe main idea for our setting is the recent symmetric Gauss-Seidel (sGS) technique which is developed for solving the multi-block convex composite problem. This idea also enables us to build the equivalence between the proposed method and the well-known accelerated proximal… Show more

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References 62 publications
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