4 September 2009 Self-similar random vector fields and their wavelet analysis
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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.
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Pouya Dehghani Tafti, Michael Unser, "Self-similar random vector fields and their wavelet analysis", Proc. SPIE 7446, Wavelets XIII, 74460Y (4 September 2009); doi: 10.1117/12.824873; https://doi.org/10.1117/12.824873
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