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Journal of Mathematical Imaging and Vision

, Volume 38, Issue 1, pp 52–69 | Cite as

Anisotropic Smoothness Classes: From Finite Element Approximation to Image Models

  • Jean-Marie Mirebeau
  • Albert Cohen
Article

Abstract

We propose and study quantitative measures of smoothness f A(f) which are adapted to anisotropic features such as edges in images or shocks in PDE’s. These quantities govern the rate of approximation by adaptive finite elements, when no constraint is imposed on the aspect ratio of the triangles, the simplest example being \(A_{p}(f)=\|\sqrt{|\mathrm{det}(d^{2}f)|}\|_{L^{\tau}}\) which appears when approximating in the L p norm by piecewise linear elements when \(\frac{1}{\tau}=\frac{1}{p}+1\). The quantities A(f) are not semi-norms, and therefore cannot be used to define linear function spaces. We show that these quantities can be well defined by mollification when f has jump discontinuities along piecewise smooth curves. This motivates for using them in image processing as an alternative to the frequently used total variation semi-norm which does not account for the smoothness of the edges.

Keywords

Image modeling Smoothness classes Adaptive finite element approximation 

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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.UMR 7598, Laboratoire Jacques-Louis LionsUPMC Univ Paris 06ParisFrance
  2. 2.UMR 7598, Laboratoire Jacques-Louis LionsCNRSParisFrance

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