Image Deblur in Gradient Domain

Chen, X; Yang, J; Wu, Q

Image Deblur in Gradient Domain

Chen, X Yang, J Wu, Q

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Publisher:: SPIE Digital Library
Publication Type:: Journal Article
Citation:: Chen Xiaogang, Yang Jie, and Wu Qiang 2010, 'Image Deblur in Gradient Domain', SPIE Digital Library, vol. 49, no. 11, pp. 117003-1-117003-7.
Issue Date:: 2010

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Field	Value	Language
dc.contributor.author	Chen, X	en_US
dc.contributor.author	Yang, J	en_US
dc.contributor.author	Wu, Q	en_US
dc.date.accessioned	2012-02-02T04:39:59Z
dc.date.available	2012-02-02T04:39:59Z
dc.date.issued	2010	en_US
dc.identifier	2010001257	en_US
dc.identifier.citation	Chen Xiaogang, Yang Jie, and Wu Qiang 2010, 'Image Deblur in Gradient Domain', SPIE Digital Library, vol. 49, no. 11, pp. 117003-1-117003-7.	en_US
dc.identifier.issn	0091-3286	en_US
dc.identifier.other	C1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14553
dc.description.abstract	This paper proposes a new method for natural-image deblur based on a single blurred image. The natural image prior, a sparse gradient distribution, is enforced using a gradient histogram remapping method in the proposed deblur algorithm. The proposed objective function for blind deconvolution is solved by an alternating minimization method. The point spread function and the unblurred image are updated alternately. The proposed method is able to produce high-quality deblurred results with low computational costs. Both synthetic and real blurred images are tested in the experiments. Encouraging experimental results show that the newly proposed method could effectively restore images blurred by complex motion.	en_US
dc.publisher	SPIE Digital Library	en_US
dc.relation.ispartof	Verified OK	en_US
dc.relation.ispartof	Optical Engineering	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1109/TIP.2011.2160073	en_US
dc.rights	Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
dc.subject	motion deblurring; blind image deconvolution; image deconvolution; image enhancement	en_US
dc.subject.classification	Artificial Intelligence and Image Processing	en_US
dc.title	Image Deblur in Gradient Domain	en_US
dc.type	Journal article
utslib.citation.volume	49	en_US
utslib.citation.number	11	en_US
utslib.location	Wahington DC, USA	en_US
utslib.citation.startpage	117003-1	en_US
utslib.citation.endpage	117003-7	en_US
utslib.identifier.org	FEIT.School of Computing and Communications	en_US
utslib.for	080100	en_US
utslib.percentage	100	en_US
utslib.copyright.status	open_access

Abstract:

This paper proposes a new method for natural-image deblur based on a single blurred image. The natural image prior, a sparse gradient distribution, is enforced using a gradient histogram remapping method in the proposed deblur algorithm. The proposed objective function for blind deconvolution is solved by an alternating minimization method. The point spread function and the unblurred image are updated alternately. The proposed method is able to produce high-quality deblurred results with low computational costs. Both synthetic and real blurred images are tested in the experiments. Encouraging experimental results show that the newly proposed method could effectively restore images blurred by complex motion.

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http://hdl.handle.net/10453/14553