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dc.contributor.authorLenzen, Frank
dc.contributor.authorBecker, Florian
dc.contributor.authorLellmann, Jan
dc.date.accessioned2016-02-25T12:40:10Z
dc.date.available2016-02-25T12:40:10Z
dc.date.issued2013
dc.identifier.citationLenzen F, Becker F, Lellmann J (2013) Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities. Scale Space and Variational Methods in Computer Vision: 61–73. Available: http://dx.doi.org/10.1007/978-3-642-38267-3_6.
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.doi10.1007/978-3-642-38267-3_6
dc.identifier.urihttp://hdl.handle.net/10754/597460
dc.description.abstractTotal variation (TV) regularization, originally introduced by Rudin, Osher and Fatemi in the context of image denoising, has become widely used in the field of inverse problems. Two major directions of modifications of the original approach were proposed later on. The first concerns adaptive variants of TV regularization, the second focuses on higher-order TV models. In the present paper, we combine the ideas of both directions by proposing adaptive second-order TV models, including one anisotropic model. Experiments demonstrate that introducing adaptivity results in an improvement of the reconstruction error. © 2013 Springer-Verlag.
dc.description.sponsorshipWe thank Tanja Teuber and Kristian Bredies for kindlyproviding their codes. The work of J.L. was supported by Award No. KUK-I1-007-43, made by King Abdullah University of Science and Technology (KAUST),EPSRC first grant EP/J009539/1, and EPSRC/Isaac Newton Trust Small Grant.
dc.publisherSpringer Science + Business Media
dc.subjectadaptive
dc.subjectanisotropic
dc.subjectdirectional
dc.subjectsecond-order total variation
dc.subjectslope discontinuities
dc.subjectTGV
dc.subjectTV
dc.titleAdaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities
dc.typeBook Chapter
dc.identifier.journalScale Space and Variational Methods in Computer Vision
dc.contributor.institutionHeidelberg Collaboratory for Image Processing, Heidelberg, Germany
dc.contributor.institutionUniversity of Cambridge, Cambridge, United Kingdom
kaust.grant.numberKUK-I1-007-43


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