TY - CHAP
T1 - Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities
AU - Lenzen, Frank
AU - Becker, Florian
AU - Lellmann, Jan
N1 - 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.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/597460
UR - http://link.springer.com/10.1007/978-3-642-38267-3_6
UR - http://www.scopus.com/inward/record.url?scp=84884406173&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38267-3_6
DO - 10.1007/978-3-642-38267-3_6
M3 - Chapter
SN - 9783642382666
SP - 61
EP - 73
BT - Scale Space and Variational Methods in Computer Vision
PB - Springer Nature
ER -