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Function Spaces Based on Wavelet Expansions

  • Stéphane Jaffard
Part of the Applied and Numerical Harmonic Analysis book series (ANHA)

Abstract

Several extensions of Besov spaces are studied. They take into account the distributions of wavelet coefficients at each scale and the correlations between the positions of the large wavelet coefficients. These new spaces allow us to formalize two new notions: the “contour-type” functions, which display the strongest possible correlations, and the “shuffled-type” functions, which display the weakest possible correlations. These notions depend neither on the particular wavelet basis chosen nor on an a priori statistical model. Several examples taken from image and signal processing illustrate these notions.

Keywords

Function Space Wavelet Coefficient Besov Space Wavelet Basis Dyadic Cube 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Stéphane Jaffard

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