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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 three-dimensional cartoon-like images. This function class will have two smoothness parameters: one parameter \beta controlling classical smoothness and one parameter \alpha controlling anisotropic smoothness. The class then consists of piecewise C^\beta-smooth functions with discontinuities on a piecewise C^\alpha-smooth surface. We introduce a pyramid-adapted, hybrid shearlet system for the three-dimensional setting and construct frames for L^2(R^3) with this particular shearlet structure. For the smoothness range 1
Original languageEnglish
JournalArxiv.com
Publication date2011
PagesarXiv:1109.5993v1
StateE-pub ahead of print

Keywords

  • Sparse approximations, Cartoon-like images, Anisotropic features, Nonlinear approximations, Multi-dimensional data, Shearlets

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