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Geometrical and Textural Component Separation with Adaptive Scale Selection

  • Tamás Szirányi
  • Dániel Szolgay
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7252)

Abstract

The present paper addresses the cartoon/texture decomposition task, offering theoretically clear solutions for the main issues of adaptivity, structure enhancement and the quality criterion of the goal function. We apply Anisotropic Diffusion with a Total Variation based adaptive parameter estimation and automatic stopping condition. Our quality measure is based on an observation that the cartoon and the texture components of an image are orthogonal to each other. The visual and numerical comparison to the similar algorithms from the state-of-the-art showed the superiority of the proposed method.

Keywords

Sparse Representation Texture Component Texture Image Goal Function Image Decomposition 
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 2012

Authors and Affiliations

  • Tamás Szirányi
    • 1
  • Dániel Szolgay
    • 2
  1. 1.Computer and Automation Research InstituteMTA SZTAKIBudapestHungary
  2. 2.Pázmány Péter Catholic UniversityBudapestHungary

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