TY - GEN
T1 - Anisotropic third-order regularization for sparse digital elevation models
AU - Lellmann, Jan
AU - Morel, Jean-Michel
AU - Schönlieb, Carola-Bibiane
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2013
Y1 - 2013
N2 - We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.
AB - We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84884389464&origin=recordpage
U2 - 10.1007/978-3-642-38267-3_14
DO - 10.1007/978-3-642-38267-3_14
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783642382666
VL - 7893 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 161
EP - 173
BT - Scale Space and Variational Methods in Computer Vision - 4th International Conference, SSVM 2013, Proceedings
T2 - 4th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2013
Y2 - 2 June 2013 through 6 June 2013
ER -