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Wavelet-based denoising by customized thresholding

Yoon, Byung-Jun and Vaidyanathan, P. P. (2004) Wavelet-based denoising by customized thresholding. In: Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on. Vol.2. IEEE , Piscataway, NJ, pp. 925-928. ISBN 0780384849.

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The problem of estimating a signal that is corrupted by additive noise has been of interest to many researchers for practical as well as theoretical reasons. Many of the traditional denoising methods have been using linear methods such as the Wiener filtering. Recently, nonlinear methods, especially those based on wavelets have become increasingly popular, due to a number of advantages over the linear methods. It has been shown that wavelet-thresholding has near-optimal properties in the minimax sense, and guarantees better rate of convergence, despite its simplicity. Even though much work has been done in the field of wavelet-thresholding, most of it was focused on statistical modeling of the wavelet coefficients and the optimal choice of the thresholds. In this paper, we propose a custom thresholding function which can improve the denoised results significantly. Simulation results are given to demonstrate the advantage of the new thresholding function.

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Vaidyanathan, P. P.0000-0003-3003-7042
Additional Information:© 2004 IEEE. Reprinted with Permission. Work supported in part by the ONR grant N00014-99-1-1002, USA.
Subject Keywords:parameter estimation; random noise; signal denoising; wavelet transforms; Wiener filtering; additive noise; customized thresholding; nonlinear methods; signal estimation; wavelet-based denoising; wavelet-thresholding
Record Number:CaltechAUTHORS:YOOicassp04
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9705
Deposited On:05 Mar 2008
Last Modified:08 Nov 2021 21:01

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