Lipschitz and total-variational regularization for blind deconvolution

Yu-Mei Huang, Michael K. Ng*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

7 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)195-206
Number of pages12
JournalCommunications in Computational Physics
Volume4
Issue number1
Publication statusPublished - Jul 2008

Scopus Subject Areas

  • Physics and Astronomy (miscellaneous)

User-Defined Keywords

  • Lipschitz regularization
  • total variational regularization
  • blind deconvolution
  • texture
  • Poisson singular integral, alternating iterative algorithm

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