Image Deblur in Gradient Domain

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Show simple item record Chen, Xiaogang en_US Yang, Jie en_US Wu, Qiang en_US
dc.contributor.editor en_US 2012-02-02T04:39:59Z 2012-02-02T04:39:59Z 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.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.language en_US
dc.publisher SPIE Digital Library en_US
dc.relation.isbasedon 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.title Image Deblur in Gradient Domain en_US
dc.parent Optical Engineering en_US
dc.journal.volume 49 en_US
dc.journal.number 11 en_US
dc.publocation Wahington DC, USA en_US
dc.identifier.startpage 117003-1 en_US
dc.identifier.endpage 117003-7 en_US FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 0000065662 en_US
dc.personcode 0000027379 en_US
dc.personcode 000748 en_US
dc.percentage 100 en_US Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US
dc.location.activity en_US
dc.description.keywords motion deblurring; blind image deconvolution; image deconvolution; image enhancement en_US
dc.staffid 000748 en_US
utslib.copyright.status Open Access 2015-04-15 12:23:47.074767+10

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