Multiscale approximation of piecewise smooth two-dimensional functions using normal triangulated meshes

Maarten Jansen, Richard Baraniuk, Sridhar Lavu

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Multiresolution triangulation meshes are widely used in computer graphics for representing three-dimensional (3-d) shapes. We propose to use these tools to represent 2-d piecewise smooth functions such as grayscale images, because triangles have potential to more efficiently approximate the discontinuities between the smooth pieces than other standard tools like wavelets. We show that normal mesh subdivision is an efficient triangulation, thanks to its local adaptivity to the discontinuities. Indeed, we prove that, within a certain function class, the normal mesh representation has an optimal asymptotic error decay rate as the number of terms in the representation grows. This function class is the so-called horizon class comprising constant regions separated by smooth discontinuities, where the line of discontinuity is C2 continuous. This optimal decay rate is possible because normal meshes automatically generate a polyline (piecewise linear) approximation of each discontinuity, unlike the blocky piecewise constant approximation of tensor product wavelets. In this way, the proposed nonlinear multiscale normal mesh decomposition is an anisotropic representation of the 2-d function. The same idea of anisotropic representations lies at the basis of decompositions such as wedgelet and curvelet transforms, but the proposed normal mesh approach has a unique construction.

Original languageEnglish (US)
Pages (from-to)92-130
Number of pages39
JournalApplied and Computational Harmonic Analysis
Volume19
Issue number1
DOIs
StatePublished - Jul 2005

Keywords

  • Approximation
  • Image
  • Mesh
  • Multiresolution
  • Normal offsets
  • Wavelet

ASJC Scopus subject areas

  • Analysis
  • Applied Mathematics

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