Mathematical Imaging and Surface Processing

  • Antonin Chambolle

    Ecole Polytechnique, Palaiseau, France
  • Martin Rumpf

    Universität Bonn, Germany
  • Peter Schröder

    California Institute of Technology, Pasadena, USA
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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.

Cite this article

Antonin Chambolle, Martin Rumpf, Peter Schröder, Mathematical Imaging and Surface Processing. Oberwolfach Rep. 13 (2016), no. 1, pp. 155–214

DOI 10.4171/OWR/2016/4