DMCA
The Discrete Multiple Wavelet Transform and Thresholding Methods (1998)
| Venue: | IEEE Transactions in Signal Processing |
| Citations: | 37 - 3 self |
BibTeX
@ARTICLE{Silverman98thediscrete,
author = {Downie Silverman and T. R. Downie and B. W. Silverman},
title = {The Discrete Multiple Wavelet Transform and Thresholding Methods},
journal = {IEEE Transactions in Signal Processing},
year = {1998},
volume = {46},
pages = {2558--2561}
}
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Abstract
Orthogonal wavelet bases have recently been developed using multiple mother wavelet functions. Applying the discrete multiple wavelet transform requires the input data to be preprocessed to obtain a more economical decomposition. We discuss the properties of several preprocessing methods and their effect on the thresholding results. We propose a multivariate thresholding method for multiwavelets where each wavelet coefficient vector is thresholded as opposed to each element. A multiwavelet universal threshold is obtained using the asymptotic behaviour of the Ø 2 distribution. A simulation study demonstrates that when using the Geronimo multiwavelet with an appropriate preprocessing method and bivariate thresholding, better results are obtained compared with using Daubechies wavelets. 1 Introduction The development of wavelet theory has given rise to practical methods of data smoothing and data compression. These methods in general give better results than other non-parametric smooth...
Keyphrases
discrete multiple wavelet transform thresholding method multiple mother wavelet function asymptotic behaviour data compression input data thresholding result practical method multivariate thresholding method geronimo multiwavelet economical decomposition non-parametric smooth bivariate thresholding wavelet coefficient vector orthogonal wavelet base simulation study wavelet theory daubechies wavelet appropriate preprocessing method multiwavelet universal threshold
