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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 4 — Feb. 24, 2014
  • pp: 3860–3865

A L0 sparse analysis prior for blind poissonian image deconvolution

Xiaojin Gong, Baisheng Lai, and Zhiyu Xiang  »View Author Affiliations

Optics Express, Vol. 22, Issue 4, pp. 3860-3865 (2014)

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This paper proposes a new approach for blindly deconvolving images that are contaminated by Poisson noise. The proposed approach incorporates a new prior, that is the L0 sparse analysis prior, together with the total variation constraint into the maximum a posteriori (MAP) framework for deconvolution. A greedy analysis pursuit numerical scheme is exploited to solve the L0 regularized MAP problem. Experimental results show that our approach not only produces smooth results substantially suppressing artifacts and noise, but also preserves intensity changes sharply. Both quantitative and qualitative comparisons to the specialized state-of-the-art algorithms demonstrate its superiority.

© 2014 Optical Society of America

OCIS Codes
(100.1830) Image processing : Deconvolution
(100.2000) Image processing : Digital image processing
(100.3020) Image processing : Image reconstruction-restoration
(100.1455) Image processing : Blind deconvolution

ToC Category:
Image Processing

Original Manuscript: January 7, 2014
Revised Manuscript: January 31, 2014
Manuscript Accepted: February 2, 2014
Published: February 11, 2014

Xiaojin Gong, Baisheng Lai, and Zhiyu Xiang, "A L0 sparse analysis prior for blind poissonian image deconvolution," Opt. Express 22, 3860-3865 (2014)

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