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Image deblurring with impulse noise using split Bregman algorithm

  • Huazhong University of Science and Technology
  • NEC Corporation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We propose an effective method to resolve blurred images with impulse noise. Our method has two steps. First, an improved adaptive median filter is proposed for image denoising; And second, the problem of deblurring the denoised image is formulated as to minimize the object function which consists of L1 data-fedility term and double regularization term. The minimization problem is solved by split Bregman algorithm. Numerical results using image with different blurs and impulse noise show that the proposed method gives better performance than the variable splitting alternative minimization algorithm in [10] by objective peak signal to noise ratio and subjective vision quality, which demonstrates the efficiency of our proposed algorithms.

Original languageEnglish
Title of host publicationISCID 2009 - 2009 International Symposium on Computational Intelligence and Design
Pages233-238
Number of pages6
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 International Symposium on Computational Intelligence and Design, ISCID 2009 - Changsha, Hunan, China
Duration: 12 Dec 200914 Dec 2009

Publication series

NameISCID 2009 - 2009 International Symposium on Computational Intelligence and Design
Volume2

Conference

Conference2009 International Symposium on Computational Intelligence and Design, ISCID 2009
Country/TerritoryChina
CityChangsha, Hunan
Period12/12/0914/12/09

Keywords

  • Double regularization
  • Image deblurring
  • Impulse noise
  • Split bregman algorithm

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