PRIMAL DOMAIN DECOMPOSITION METHODS FOR THE TOTAL VARIATION MINIMIZATION, BASED ON DUAL DECOMPOSITION

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We propose nonoverlapping domain decomposition methods for solving the total variation minimization problem. We decompose the domain of the dual problem into nonoverlapping rectangular subdomains, where local total variation problems are solved. We convert the local dual problems into the equivalent primal forms which reproduce the original problem at smaller dimensions. Sequential and parallel algorithms are presented. The convergence of both algorithms is analyzed and numerical results are presented.
Publisher
SIAM PUBLICATIONS
Issue Date
2017
Language
English
Article Type
Article
Keywords

SUBSPACE CORRECTION METHODS; LINEAR INVERSE PROBLEMS; IMAGE-RESTORATION; THRESHOLDING ALGORITHM; RECOVERY

Citation

SIAM JOURNAL ON SCIENTIFIC COMPUTING, v.39, no.2, pp.B403 - B423

ISSN
1064-8275
DOI
10.1137/15M1049919
URI
http://hdl.handle.net/10203/224568
Appears in Collection
MA-Journal Papers(저널논문)
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