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

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

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Article ID: iaor20141419
Volume: 255
Issue: 12
Start Page Number: 580
End Page Number: 592
Publication Date: Jan 2014
Journal: Journal of Computational and Applied Mathematics
Authors: , ,
Keywords: programming: convex, heuristics
Abstract:

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.

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