Generalized Matrix Spectral Factorization and Quasi-tight Framelets with Minimum Number of Generators
Chenzhe Diao, Bin Han

TL;DR
This paper introduces a systematic approach to construct quasi-tight framelets with minimal generators from any compactly supported refinable function, by solving generalized matrix spectral factorization problems for Laurent polynomial matrices.
Contribution
It develops a new theoretical framework linking quasi-tight framelets to generalized matrix spectral factorization, enabling minimal generator construction.
Findings
Constructed quasi-tight framelets with minimal generators
Provided algorithms for spectral factorization and framelet construction
Demonstrated the approach with multiple examples
Abstract
As a generalization of orthonormal wavelets in , tight framelets (also called tight wavelet frames) are of importance in wavelet analysis and applied sciences due to their many desirable properties in applications such as image processing and numerical algorithms. Tight framelets are often derived from particular refinable functions satisfying certain stringent conditions. Consequently, a large family of refinable functions cannot be used to construct tight framelets. This motivates us to introduce the notion of a quasi-tight framelet, which is a dual framelet but behaves almost like a tight framelet. It turns out that the study of quasi-tight framelets is intrinsically linked to the problem of the generalized matrix spectral factorization for matrices of Laurent polynomials. In this paper, we provide a systematic investigation on the generalized matrix spectral factorization…
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Taxonomy
TopicsMathematical Analysis and Transform Methods · Fibroblast Growth Factor Research
