Sparse representation based blind image deblurring

Haichao Zhang, Jianchao Yang, Yanning Zhang, Thomas S. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a sparse representation based blind image deblurring method. The proposed method exploits the sparsity property of natural images, by assuming that the patches from the natural images can be sparsely represented by an over-complete dictionary. By incorporating this prior into the deblurring process, we can effectively regularize the ill-posed inverse problem and alleviate the undesirable ring effect which is usually suffered by conventional deblurring methods. Experimental results compared with state-of-the-art blind deblurring method demonstrate the effectiveness of the proposed method.

Original languageEnglish (US)
Title of host publicationElectronic Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011
DOIs
StatePublished - 2011
Event2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011 - Barcelona, Spain
Duration: Jul 11 2011Jul 15 2011

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Other

Other2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011
Country/TerritorySpain
CityBarcelona
Period7/11/117/15/11

Keywords

  • blind image deblurring
  • deconvolution
  • sparse representation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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