Conditional gradient Tikhonov method for a convex optimization problem in image restoration
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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.
论文关键词:Convex programming,Optimization,Image restoration,Discrete ill-posed problem,Tikhonov regularization
论文评审过程:Received 8 April 2012, Revised 20 December 2012, Available online 18 June 2013.
论文官网地址:https://doi.org/10.1016/j.cam.2013.06.011