Oberwolfach Reports


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Volume 13, Issue 1, 2016, pp. 155–214
DOI: 10.4171/OWR/2016/4

Published online: 2016-10-11

Mathematical Imaging and Surface Processing

Antonin Chambolle[1], Martin Rumpf[2] and Peter Schröder[3]

(1) Ecole Polytechnique, Palaiseau, France
(2) Universität Bonn, Germany
(3) California Institute of Technology, Pasadena, USA

Within the last decade image and geometry processing have become increasingly rigorous with solid foundations in mathematics. Both areas are research fields at the intersection of different mathematical disciplines, ranging from geometry and calculus of variations to PDE analysis and numerical analysis. The workshop brought together scientists from all these areas and a fruitful interplay took place. There was a lively exchange of ideas between geometry and image processing applications areas, characterized in a number of ways in this workshop. For example, optimal transport, first applied in computer vision is now used to define a distance measure between 3d shapes, spectral analysis as a tool in image processing can be applied in surface classification and matching, and so on. We have also seen the use of Riemannian geometry as a powerful tool to improve the analysis of multivalued images.

This volume collects the abstracts for all the presentations covering this wide spectrum of tools and application domains.

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Chambolle Antonin, Rumpf Martin, Schröder Peter: Mathematical Imaging and Surface Processing. Oberwolfach Rep. 13 (2016), 155-214. doi: 10.4171/OWR/2016/4