http://dx.doi.org/10.1137/090774823">
 

Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Solving constrained total-variation image restoration and reconstruction problems via alternating direction methods

Language

English

Abstract

In this paper, we study alternating direction methods for solving constrained totalvariation image restoration and reconstruction problems. Alternating direction methods can be implementable variants of the classical augmented Lagrangian method for optimization problems with separable structures and linear constraints. The proposed framework allows us to solve problems of image restoration, impulse noise removal, inpainting, and image cartoon+texture decomposition. As the constrained model is employed, we need only to input the noise level, and the estimation of the regularization parameter is not required in these imaging problems. Experimental results for such imaging problems are presented to illustrate the effectiveness of the proposed method. We show that the alternating direction method is very efficient for solving image restoration and reconstruction problems. © 2010 Society for Industrial and Applied Mathematics.

Keywords

Alternating direction method, Augmented Lagrangian, Image reconstruction, Image restoration, Total-variation

Publication Date

2010

Source Publication Title

SIAM Journal on Scientific Computing

Volume

32

Issue

5

Start Page

2710

End Page

2736

Publisher

Society for Industrial and Applied Mathematics

ISSN (print)

10648275

ISSN (electronic)

10957197

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