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Combing a Porcupine via Stereographic Direction Difusion

  • Nir A. Sochen
  • Ron Kimmel
Conference paper
Part of the Lecture Notes in Computer Science 2106 book series (LNCS, volume 2106)

Abstract

This paper addresses the problem of feature enhancement in noisy images when the feature is known to be constrained to a manifold. As an example, we study the problem of direction denoising. This problem was treated recently and several solutions were proposed. The various solutions share the same structure. They are composed of two terms: A difusion term and a projection term. Analytically, the solutions differ in the difusion part. The projection part is equivalent in all works. Yet, as it is often the case, the analytically equivalent projection terms differ from a numerical viewpoint. We present in this work a new parameterization of the problem that enables us to work always in a numerically stable way.

Keywords

Noisy Image Switching Point Riemannian Structure South Hemisphere Polyakov Action 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Nir A. Sochen
    • 1
  • Ron Kimmel
    • 2
  1. 1.Department of Applied MathematicsUniversity of Tel AvivTel-AvivIsrael
  2. 2.Department of Computer ScienceTechnion - Israel Institute of TechnologyHaifaIsrael

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