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Article: Coupled variational image decomposition and restoration model for blurred cartoon-plus-texture images with missing pixels

TitleCoupled variational image decomposition and restoration model for blurred cartoon-plus-texture images with missing pixels
Authors
KeywordsCartoon and texture
deblurring
image decomposition
variable splitting method
Issue Date2013
Citation
IEEE Transactions on Image Processing, 2013, v. 22, n. 6, p. 2233-2246 How to Cite?
AbstractIn this paper, we develop a decomposition model to restore blurred images with missing pixels. Our assumption is that the underlying image is the superposition of cartoon and texture components. We use the total variation norm and its dual norm to regularize the cartoon and texture, respectively. We recommend an efficient numerical algorithm based on the splitting versions of augmented Lagrangian method to solve the problem. Theoretically, the existence of a minimizer to the energy function and the convergence of the algorithm are guaranteed. In contrast to recently developed methods for deblurring images, the proposed algorithm not only gives the restored image, but also gives a decomposition of cartoon and texture parts. These two parts can be further used in segmentation and inpainting problems. Numerical comparisons between this algorithm and some state-of-the-art methods are also reported. © 1992-2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/251029
ISSN
2023 Impact Factor: 10.8
2023 SCImago Journal Rankings: 3.556
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorNg, Michael K.-
dc.contributor.authorYuan, Xiaoming-
dc.contributor.authorZhang, Wenxing-
dc.date.accessioned2018-02-01T01:54:22Z-
dc.date.available2018-02-01T01:54:22Z-
dc.date.issued2013-
dc.identifier.citationIEEE Transactions on Image Processing, 2013, v. 22, n. 6, p. 2233-2246-
dc.identifier.issn1057-7149-
dc.identifier.urihttp://hdl.handle.net/10722/251029-
dc.description.abstractIn this paper, we develop a decomposition model to restore blurred images with missing pixels. Our assumption is that the underlying image is the superposition of cartoon and texture components. We use the total variation norm and its dual norm to regularize the cartoon and texture, respectively. We recommend an efficient numerical algorithm based on the splitting versions of augmented Lagrangian method to solve the problem. Theoretically, the existence of a minimizer to the energy function and the convergence of the algorithm are guaranteed. In contrast to recently developed methods for deblurring images, the proposed algorithm not only gives the restored image, but also gives a decomposition of cartoon and texture parts. These two parts can be further used in segmentation and inpainting problems. Numerical comparisons between this algorithm and some state-of-the-art methods are also reported. © 1992-2012 IEEE.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Image Processing-
dc.subjectCartoon and texture-
dc.subjectdeblurring-
dc.subjectimage decomposition-
dc.subjectvariable splitting method-
dc.titleCoupled variational image decomposition and restoration model for blurred cartoon-plus-texture images with missing pixels-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TIP.2013.2246520-
dc.identifier.scopuseid_2-s2.0-84875853070-
dc.identifier.volume22-
dc.identifier.issue6-
dc.identifier.spage2233-
dc.identifier.epage2246-
dc.identifier.isiWOS:000318477500011-
dc.identifier.issnl1057-7149-

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