Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities

Frank Lenzen, Florian Becker, Jan Lellmann

Research output: Chapter in Book/Report/Conference proceedingChapter

13 Scopus citations


Total 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.
Original languageEnglish (US)
Title of host publicationScale Space and Variational Methods in Computer Vision
PublisherSpringer Nature
Number of pages13
ISBN (Print)9783642382666
StatePublished - 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-I1-007-43
Acknowledgements: We 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.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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