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Proceedings Paper

Self-similar random vector fields and their wavelet analysis
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Paper Abstract

This paper is concerned with the mathematical characterization and wavelet analysis of self-similar random vector fields. The study consists of two main parts: the construction of random vector models on the basis of their invariance under coordinate transformations, and a study of the consequences of conducting a wavelet analysis of such random models. In the latter part, after briefly examining the effects of standard wavelets on the proposed random fields, we go on to introduce a new family of Laplacian-like vector wavelets that in a way duplicate the covariant-structure and whitening relations governing our random models.

Paper Details

Date Published: 4 September 2009
PDF: 8 pages
Proc. SPIE 7446, Wavelets XIII, 74460Y (4 September 2009); doi: 10.1117/12.824873
Show Author Affiliations
Pouya Dehghani Tafti, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Michael Unser, Ecole Polytechnique Fédérale de Lausanne (Switzerland)


Published in SPIE Proceedings Vol. 7446:
Wavelets XIII
Vivek K. Goyal; Manos Papadakis; Dimitri Van De Ville, Editor(s)

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