Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

Jan Lellmann, Jean-Michel Morel, Carola-Bibiane Schönlieb

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Scopus citations

Abstract

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.
Original languageEnglish (US)
Title of host publicationScale Space and Variational Methods in Computer Vision
PublisherSpringer Nature
Pages161-173
Number of pages13
ISBN (Print)9783642382666
DOIs
StatePublished - 2013
Externally publishedYes

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