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Optimally sparse image representation by the easy path wavelet transform, preprint

By Gerlind Plonka, Stefanie Tenorth and Armin Iske

Abstract

The Easy Path Wavelet Transform (EPWT) [20] has recently been proposed by one of the authors as a tool for sparse representations of bivariate functions from discrete data, in particular from image data. The EPWT is a locally adaptive wavelet transform. It works along pathways through the array of function values and it exploits the local correlations of the given data in a simple appropriate manner. In this paper, we show that the EPWT leads, for a suitable choice of the pathways, to optimal N-term approximations for piecewise Hölder continuous functions with singularities along curves

Topics: Key words. sparse data representation
Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.308.6532
Provided by: CiteSeerX
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