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A Robust Algorithm for Blind Total Variation Restoration
作者单位:Jing Xu~1 Qian-shun Chang~2 1 School of Statistics and Mathematics,Zhejiang Gongshang University,Hangzhou 310018,China 2 Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China
摘    要:Image restoration is a fundamental problem in image processing. Blind image restoration has a great value in its practical application. However, it is not an easy problem to solve due to its complexity and difficulty. In this paper, we combine our robust algorithm for known blur operator with an alternating minimization implicit iterative scheme to deal with blind deconvolution problem, recover the image and identify the point spread function(PSF). The only assumption needed is satisfy the practical physical sense. Numerical experiments demonstrate that this minimization algorithm is efficient and robust over a wide range of PSF and have almost the same results compared with known PSF algorithm.

关 键 词:解卷积  总变差  代数重度法  加速度

A robust algorithm for blind total variation restoration
Authors:Jing Xu  Qian-shun Chang
Institution:[1]School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China [2]Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Deijing 100190, China
Abstract:Image restoration is a fundamental problem in image processing. Blind image restoration has a great value in its practical application. However, it is not an easy problem to solve due to its complexity and difficulty. In this paper, we combine our robust algorithm for known blur operator with an alternating minimization implicit iterative scheme to deal with blind deconvolution problem, recover the image and identify the point spread function(PSF). The only assumption needed is satisfy the practical physical sense. Numerical experiments demonstrate that this minimization algorithm is efficient and robust over a wide range of PSF and have almost the same results compared with known PSF algorithm.
Keywords:Blind deconvolution  total variation  algebraic multigrid method  Krylov acceleration
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