Maximum a posteriori blind image deconvolution with Huber–Markov random-field regularization
Optics Letters, Vol. 34, Issue 9, pp. 1453-1455 (2009)
http://dx.doi.org/10.1364/OL.34.001453
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Abstract
We propose a maximum a posteriori blind deconvolution approach using a Huber–Markov random-field model. Compared with the conventional maximum-likelihood method, our algorithm not only suppresses noise effectively but also significantly alleviates the artifacts produced by the deconvolution process. The performance of this method is demonstrated by computer simulations.
© 2009 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
(100.3190) Image processing : Inverse problems
(100.1455) Image processing : Blind deconvolution
ToC Category:
Image Processing
History
Original Manuscript: January 9, 2009
Revised Manuscript: April 7, 2009
Manuscript Accepted: April 7, 2009
Published: April 30, 2009
Citation
Zhimin Xu and Edmund Y. Lam, "Maximum a posteriori blind image deconvolution with Huber–Markov random-field regularization," Opt. Lett. 34, 1453-1455 (2009)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-34-9-1453
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