Image Recovery by Decomposition with Component-Wise Regularization

Shunsuke ONO  Takamichi MIYATA  Isao YAMADA  Katsunori YAMAOKA  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E95-A   No.12   pp.2470-2478
Publication Date: 2012/12/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E95.A.2470
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Image
image recovery,  decomposition,  regularization,  sparsity,  convex optimization,  alternating direction method of multipliers (ADMM),  

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Solving image recovery problems requires the use of some efficient regularizations based on a priori information with respect to the unknown original image. Naturally, we can assume that an image is modeled as the sum of smooth, edge, and texture components. To obtain a high quality recovered image, appropriate regularizations for each individual component are required. In this paper, we propose a novel image recovery technique which performs decomposition and recovery simultaneously. We formulate image recovery as a nonsmooth convex optimization problem and design an iterative scheme based on the alternating direction method of multipliers (ADMM) for approximating its global minimizer efficiently. Experimental results reveal that the proposed image recovery technique outperforms a state-of-the-art method.