Conditional gradient Tikhonov method for a convex optimization problem in image restoration

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:255

Article

Bouhamidi, A.¹  Enkhbat, R.²  Jbilou, K.¹ 

[1] Univ Littoral, LMPA, F-62228 Calais, France

[2] Natl Univ Mongolia, Ulaanbaatar, Mongolia

关键词: Convex programming;    Optimization;    Image restoration;    Discrete ill-posed problem;    Tikhonov regularization;   

DOI  :  10.1016/j.cam.2013.06.011

来源: Elsevier

【 摘 要 】

In this paper, we consider the problem of image restoration with Tikhonov regularization as a convex constrained minimization problem. Using a Kronecker decomposition of the blurring matrix and the Tikhonov regularization matrix, we reduce the size of the image restoration problem. Therefore, we apply the conditional gradient method combined with the Tikhonov regularization technique and derive a new method. We demonstrate the convergence of this method and perform some numerical examples to illustrate the effectiveness of the proposed method as compared to other existing methods. (C) 2013 Elsevier B.V. All rights reserved.

【 授权许可】

Free