Optimally sparse approximations of 3D functions by compactly supported shearlet frames

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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We study efficient and reliable methods of capturing and sparsely representing anisotropic structures in 3D data. As a model class for multidimensional data with anisotropic features, we introduce generalized 3D cartoon-like images. This function class will have two smoothness parameters: one parameter β controlling classical smoothness and one parameter α controlling anisotropic smoothness. The class then consists of piecewise C β-smooth functions with discontinuities on a piecewise C α-smooth surface. We introduce a pyramid-adapted, hybrid shearlet system for the 3D setting and construct frames for L 2(ℝ3) with this particular shearlet structure. For the smoothness range 1 <α ≤ β ≤ 2 we show that pyramid-adapted shearlet systems provide a nearly optimally sparse approximation rate within the generalized cartoon-like image model class measured by means of nonlinear N-term approximations. © 2012 Society for Industrial and Applied Mathematics.
Original languageEnglish
JournalS I A M Journal on Mathematical Analysis
Publication date2012
Volume44
Issue4
Pages2962-3017
ISSN0036-1410
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 5

Keywords

  • Anisotropy, Three dimensional
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