A generalized parametric PR-QMF design technique based on Bernstein polynomial approximation

Author

Caglar, Hakan ; Akansu, Ali N.

Author_Institution

Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

41

Issue

7

fYear

1993

fDate

7/1/1993 12:00:00 AM

Firstpage

2314

Lastpage

2321

Abstract

A generalized, parametric, perfect-reconstruction quadrature-mirror-filter (PR-QMF) design technique based on Bernstein polynomial approximation in the magnitude-square domain is presented. The parametric nature of this solution provides useful insights to the PR-QMF problem. Several well-known orthonormal wavelet filters, PR-QMFs, are shown to be the special cases of the proposed technique. Energy compaction performances of a few popular signal decomposition techniques are presented for AR(1) signal sources. It is observed that the hierarchical QMF filter banks considered outperform the block transforms as expected

Keywords

digital filters; filtering and prediction theory; polynomials; signal processing; wavelet transforms; AR(1) signal sources; Bernstein polynomial approximation; energy compaction performance; generalized parametric PR-QMF design technique; hierarchical QMF filter banks; magnitude-square domain; orthonormal wavelet filters; perfect-reconstruction quadrature-mirror-filter; signal decomposition techniques; Compaction; Energy resolution; Filter bank; Frequency; Image reconstruction; Mirrors; Polynomials; Signal representations; Signal resolution; Tree data structures;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.224242

Filename

224242