Volume 28, Issue 6
Block-Triangular Preconditioners for Systems Arising from Edge-Preserving Image Restoration

Zhong-Zhi Bai, Yu-Mei Huang & Michael K. Ng

J. Comp. Math., 28 (2010), pp. 848-863.

Published online: 2010-12

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  • Abstract

Signal and image restoration problems are often solved by minimizing a cost function consisting of an $\ell_2$ data-fidelity term and a regularization term. We consider a class of convex and edge-preserving regularization functions. In specific, half-quadratic regularization as a fixed-point iteration method is usually employed to solve this problem. The main aim of this paper is to solve the above-described signal and image restoration problems with the half-quadratic regularization technique by making use of the Newton method. At each iteration of the Newton method, the Newton equation is a structured system of linear equations of a symmetric positive definite coefficient matrix, and may be efficiently solved by the preconditioned conjugate gradient method accelerated with the modified block SSOR preconditioner. Our experimental results show that the modified block-SSOR preconditioned conjugate gradient method is feasible and effective for further improving the numerical performance of the half-quadratic regularization approach.

  • Keywords

Block system of equations, Matrix preconditioner, Edge-preserving, Image restoration, Half-quadratic regularization.

  • AMS Subject Headings

65C20, 65F10.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-28-848, author = {}, title = {Block-Triangular Preconditioners for Systems Arising from Edge-Preserving Image Restoration}, journal = {Journal of Computational Mathematics}, year = {2010}, volume = {28}, number = {6}, pages = {848--863}, abstract = {

Signal and image restoration problems are often solved by minimizing a cost function consisting of an $\ell_2$ data-fidelity term and a regularization term. We consider a class of convex and edge-preserving regularization functions. In specific, half-quadratic regularization as a fixed-point iteration method is usually employed to solve this problem. The main aim of this paper is to solve the above-described signal and image restoration problems with the half-quadratic regularization technique by making use of the Newton method. At each iteration of the Newton method, the Newton equation is a structured system of linear equations of a symmetric positive definite coefficient matrix, and may be efficiently solved by the preconditioned conjugate gradient method accelerated with the modified block SSOR preconditioner. Our experimental results show that the modified block-SSOR preconditioned conjugate gradient method is feasible and effective for further improving the numerical performance of the half-quadratic regularization approach.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1001.m2729}, url = {http://global-sci.org/intro/article_detail/jcm/8554.html} }
TY - JOUR T1 - Block-Triangular Preconditioners for Systems Arising from Edge-Preserving Image Restoration JO - Journal of Computational Mathematics VL - 6 SP - 848 EP - 863 PY - 2010 DA - 2010/12 SN - 28 DO - http://doi.org/10.4208/jcm.1001.m2729 UR - https://global-sci.org/intro/article_detail/jcm/8554.html KW - Block system of equations, Matrix preconditioner, Edge-preserving, Image restoration, Half-quadratic regularization. AB -

Signal and image restoration problems are often solved by minimizing a cost function consisting of an $\ell_2$ data-fidelity term and a regularization term. We consider a class of convex and edge-preserving regularization functions. In specific, half-quadratic regularization as a fixed-point iteration method is usually employed to solve this problem. The main aim of this paper is to solve the above-described signal and image restoration problems with the half-quadratic regularization technique by making use of the Newton method. At each iteration of the Newton method, the Newton equation is a structured system of linear equations of a symmetric positive definite coefficient matrix, and may be efficiently solved by the preconditioned conjugate gradient method accelerated with the modified block SSOR preconditioner. Our experimental results show that the modified block-SSOR preconditioned conjugate gradient method is feasible and effective for further improving the numerical performance of the half-quadratic regularization approach.

Zhong-Zhi Bai, Yu-Mei Huang & Michael K. Ng. (1970). Block-Triangular Preconditioners for Systems Arising from Edge-Preserving Image Restoration. Journal of Computational Mathematics. 28 (6). 848-863. doi:10.4208/jcm.1001.m2729
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