Fast continuous wavelet transform

Authors:
M. Vrhel;Chulhee Lee;I. Unser
Affiliations:
Biomed. Eng. & Instrum. Program, Nat. Inst. of Health, Bethesda, MD, USA;Biomed. Eng. & Instrum. Program, Nat. Inst. of Health, Bethesda, MD, USA;Biomed. Eng. & Instrum. Program, Nat. Inst. of Health, Bethesda, MD, USA
Venue:
ICASSP '95 Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02
Year:
1995

Citing 0
Cited 1

The convolution theorem for the continuous wavelet tranform

Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

We introduce a general framework for the efficient computation of the continuous wavelet transform (CWT). The method allows arbitrary sampling along the scale axis, and achieves O(N) complexity per scale where N is the length of the signal. Our approach makes use of a compactly supported scaling function to approximate the analyzing wavelet. We derive error bounds on the wavelet approximation and show how to obtain any desired level of accuracy through the use of higher order representations. Finally, we present examples of implementation for different wavelets using polynomial spline approximations.