full
search.png

Search

close.png

Cancel

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

Yu-Mei Huang & Michael K. Ng

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

Published online: 2008-04

Preview Full PDF 3155 28702

Cited by

google scholar semantic scholar
Export citation
  • Abstract

In [3], Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind 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. 

  • Keywords

  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@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 spread functions in blind 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} }
TY - JOUR T1 - Lipschitz and Total-Variational Regularization for Blind Deconvolution AU - Yu-Mei Huang & Michael K. Ng JO - Communications in Computational Physics VL - 1 SP - 195 EP - 206 PY - 2008 DA - 2008/04 SN - 4 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/cicp/7787.html KW - AB -

In [3], Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind 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. 

Yu-Mei Huang and Michael K. Ng. (2008). Lipschitz and Total-Variational Regularization for Blind Deconvolution. Communications in Computational Physics. 4 (1). 195-206. doi:
Copy to clipboard
BibteX RIS TXT
The citation has been copied to your clipboard