Complex Wavelets for Shift Invariant Analysis and Filtering of Signals

Author: Kingsbury N.

Source: Applied and Computational Harmonic Analysis, Volume 10, Number 3, May 2001 , pp. 234-253(20)

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Abstract:

This paper describes a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. This introduces limited redundancy (2^m:1 for m-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. Here we analyze why the new transform can be designed to be shift invariant and describe how to estimate the accuracy of this approximation and design suitable filters to achieve this. We discuss two different variants of the new transform, based on odd/even and quarter-sample shift (Q-shift) filters, respectively. We then describe briefly how the dual tree may be extended for images and other multi-dimensional signals, and finally summarize a range of applications of the transform that take advantage of its unique properties. Copyright 2001 Academic Press

Language: English

Document Type: Research article

Affiliations: Signal Processing Group, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom

Publication date: 2001-05-01