TY - GEN
T1 - Anisotropic third-order regularization for sparse digital elevation models
AU - LELLMANN, Jan
AU - MOREL, Jean-Michel
AU - SCHÖNLIEB, Carola Bibiane
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.
UR - https://www.scopus.com/pages/publications/84884389464
U2 - 10.1007/978-3-642-38267-3_14
DO - 10.1007/978-3-642-38267-3_14
M3 - Conference paper (refereed)
AN - SCOPUS:84884389464
SN - 9783642382666
T3 - Lecture Notes in Computer Science
SP - 161
EP - 173
BT - Scale Space and Variational Methods in Computer Vision, 4th International Conference, SSVM 2013, Proceedings
PB - IEEE
T2 - 4th International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2013
Y2 - 2 June 2013 through 6 June 2013
ER -