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Article: On semismooth Newton's methods for total variation minimization

TitleOn semismooth Newton's methods for total variation minimization
Authors
Ng, Michael K.Qi, LiqunYang, Yu FeiHuang, Yu Mei
KeywordsSemismooth Newton's methods
Regularization
Denoising
Total variation
Issue Date2007
Citation
Journal of Mathematical Imaging and Vision, 2007, v. 27, n. 3, p. 265-276 How to Cite?
DOI: http://dx.doi.org/10.1007/s10851-007-0650-0
AbstractIn [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton's methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms. © Springer Science + Business Media, LLC 2007.
Persistent Identifierhttp://hdl.handle.net/10722/276807
ISSN
0924-9907
2021 Impact Factor: 1.627
2020 SCImago Journal Rankings: 0.504
ISI Accession Number ID
WOS:000245977600006

 

DC FieldValueLanguage
dc.contributor.authorNg, Michael K.-
dc.contributor.authorQi, Liqun-
dc.contributor.authorYang, Yu Fei-
dc.contributor.authorHuang, Yu Mei-
dc.date.accessioned2019-09-18T08:34:43Z-
dc.date.available2019-09-18T08:34:43Z-
dc.date.issued2007-
dc.identifier.citationJournal of Mathematical Imaging and Vision, 2007, v. 27, n. 3, p. 265-276-
dc.identifier.issn0924-9907-
dc.identifier.urihttp://hdl.handle.net/10722/276807-
dc.description.abstractIn [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton's methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms. © Springer Science + Business Media, LLC 2007.-
dc.languageeng-
dc.relation.ispartofJournal of Mathematical Imaging and Vision-
dc.subjectSemismooth Newton's methods-
dc.subjectRegularization-
dc.subjectDenoising-
dc.subjectTotal variation-
dc.titleOn semismooth Newton's methods for total variation minimization-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s10851-007-0650-0-
dc.identifier.scopuseid_2-s2.0-34247549668-
dc.identifier.volume27-
dc.identifier.issue3-
dc.identifier.spage265-
dc.identifier.epage276-
dc.identifier.isiWOS:000245977600006-
dc.identifier.issnl0924-9907-

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