There are several well known constructions of bivariate, compactly supported wavelets based on orthogonal refinable functions with dilation matrices of determinant 2 or -2. The corresponding filterbank consists of only two subbands: low-pass and high-pass. We unify these constructions and express their intrinsic structure via normal forms of the corresponding bivariate polyphase representations. A normal form is sparse and is obtained from the polyphase representation via a suitable unitary transformation. We characterize certain normal forms of bi-degree (1,1) and (2,2) and show that their non-zero elements correspond to the solutions of the univariate Quadrature Mirror Filter conditions. The unitary transformations are chosen to ensure sum rule conditions of certain order. We illustrate our results on some examples and address the quest for characterizing bivariate wavelet constructions of higher bi-degree.

Bivariate two-band wavelets demystified / Charina M.; Conti C.; Cotronei M.; Sauer T.. - In: LINEAR ALGEBRA AND ITS APPLICATIONS. - ISSN 0024-3795. - STAMPA. - 608:(2021), pp. 13-36. [10.1016/j.laa.2020.08.013]

Bivariate two-band wavelets demystified

Conti C.;
2021

Abstract

There are several well known constructions of bivariate, compactly supported wavelets based on orthogonal refinable functions with dilation matrices of determinant 2 or -2. The corresponding filterbank consists of only two subbands: low-pass and high-pass. We unify these constructions and express their intrinsic structure via normal forms of the corresponding bivariate polyphase representations. A normal form is sparse and is obtained from the polyphase representation via a suitable unitary transformation. We characterize certain normal forms of bi-degree (1,1) and (2,2) and show that their non-zero elements correspond to the solutions of the univariate Quadrature Mirror Filter conditions. The unitary transformations are chosen to ensure sum rule conditions of certain order. We illustrate our results on some examples and address the quest for characterizing bivariate wavelet constructions of higher bi-degree.
2021
608
13
36
Goal 9: Industry, Innovation, and Infrastructure
Charina M.; Conti C.; Cotronei M.; Sauer T.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1206824
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