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Konferensartikel2012Vetenskapligt granskad

A Novel Algorithm for Computing Riemannian Geodesic Distance in Rectangular 2D Grids

Nilsson, Ola; Reimers, Martin; Museth, Ken; Brun, Anders

Sammanfattning

We present a novel way to efficiently compute Riemannian geodesic distance over a two-dimensional domain. It is based on a previ- ously presented method for computation of geodesic distances on surface meshes. Our method is adapted for rectangular grids, equipped with a variable anisotropic metric tensor. Processing and visualization of such tensor fields is common in certain applications, for instance structure ten- sor fields in image analysis and diffusion tensor fields in medical imaging. The included benchmark study shows that our method provides signif- icantly better results in anisotropic regions and is faster than current stat-of-the-art solvers. Additionally, our method is straightforward to code; the test implementation is less than 150 lines of C++ code.

Publicerad i

Lecture Notes in Computer Science
2012, Volym: 7432, sidor: 265-274
Titel: Advances in Visual Computing: 8th International Symposium, ISVC 2012, Rethymnon, Crete, Greece, July 16-18, 2012, Revised Selected Papers, Part II
ISBN: 978-3-642-33190-9, eISBN: 978-3-642-33191-6
Utgivare: Springer Berlin Heidelberg

Konferens

8th International Symposium on Visual Computing (ISVC), JUL 16-18, 2012, Rethymnon, GREECE

      SLU författare

    • Brun, Anders

      • Centre for Image Analysis, Sveriges lantbruksuniversitet

    UKÄ forskningsämne

    Datavetenskap (datalogi)

    Publikationens identifierare

    DOI: https://doi.org/10.1007/978-3-642-33191-6_26

    Permanent länk till denna sida (URI)

    https://res.slu.se/id/publ/43702