Volume 4, Issue 1
Lipschitz and Total-variational Regularization for Blind Deconvolution

Yu-Mei Huang & Michael K. Ng

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Commun. Comput. Phys., 4 (2008), pp. 195-206.

Published online: 2008-04

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  • Abstract

In [3], Chan and Wong proposed to use total variational regularization for both images and point spreadfunctions inblind deconvolution. Their experimental results show that the detail of the restored images cannot be recovered. In this paper, we consider images in Lipschitz spaces, and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution. Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well. 

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@Article{CiCP-4-195, author = {Yu-Mei Huang and Michael K. Ng}, title = {Lipschitz and Total-variational Regularization for Blind Deconvolution}, journal = {Communications in Computational Physics}, year = {2008}, volume = {4}, number = {1}, pages = {195--206}, abstract = {

In [3], Chan and Wong proposed to use total variational regularization for both images and point spreadfunctions inblind deconvolution. Their experimental results show that the detail of the restored images cannot be recovered. In this paper, we consider images in Lipschitz spaces, and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution. Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well. 

}, issn = {1991-7120}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/cicp/7787.html} }
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