Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74765
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dc.contributorDepartment of Computing-
dc.creatorDeng, H-
dc.creatorRen, D-
dc.creatorXiao, G-
dc.creatorZhang, D-
dc.creatorZuo, W-
dc.date.accessioned2018-03-29T09:33:49Z-
dc.date.available2018-03-29T09:33:49Z-
dc.identifier.issn1024-123Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/74765-
dc.language.isoenen_US
dc.publisherHindawi Limiteden_US
dc.rightsCopyright © 2017 Hong Deng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following article: Hong Deng, Dongwei Ren, Gang Xiao, David Zhang, and Wangmeng Zuo, “A Coordinate Descent Method for Total Variation Minimization,” Mathematical Problems in Engineering, vol. 2017, Article ID 3012910, 13 pages, 2017 is available at https://doi.org/10.1155/2017/3012910.en_US
dc.titleA coordinate descent method for total variation minimizationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2017en_US
dc.identifier.doi10.1155/2017/3012910en_US
dcterms.abstractTotal variation (TV) is a well-known image model with extensive applications in various images and vision tasks, for example, denoising, deblurring, superresolution, inpainting, and compressed sensing. In this paper, we systematically study the coordinate descent (CoD) method for solving general total variation (TV) minimization problems. Based on multidirectional gradients representation, the proposed CoD method provides a unified solution for both anisotropic and isotropic TV-based denoising (CoDenoise). With sequential sweeping and small random perturbations, CoDenoise is efficient in denoising and empirically converges to optimal solution. Moreover, CoDenoise also delivers new perspective on understanding recursive weighted median filtering. By incorporating with the Augmented Lagrangian Method (ALM), CoD was further extended to TV-based image deblurring (ALMCD). The results on denoising and deblurring validate the efficiency and effectiveness of the CoD-based methods.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMathematical problems in engineering, 2017, v. 2017, 3012910-
dcterms.isPartOfMathematical problems in engineering-
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85030758813-
dc.identifier.eissn1563-5147en_US
dc.identifier.artn3012910en_US
dc.description.validate201811_a bcmaen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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