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Proceedings Paper

Adaptive wavelet threshold selection using higher-order statistics for signal denoising
Author(s): Samuel Peter Kozaitis; Abdullah A. Basuhail
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Paper Abstract

We used a higher-order correlation-based method for signal denoising. In our approach, we applied a third-order correlation technique for identification of wavelet coefficients uncorrupted by noise by considering triple correlation coefficients of wavelet-signal correlations for thresholding. Because the higher second-order moments of the Gaussian probability function are zero, the third-order correlation coefficient will not have statistical contribution from Gaussian noise under certain conditions. Therefore, in our approach, we examined correlation coefficients in an environment where the noise had been reduced. Our results compared favorably and was less sensitive to threshold selection when compared to a more common denoising method.

Paper Details

Date Published: 26 March 1998
PDF: 7 pages
Proc. SPIE 3391, Wavelet Applications V, (26 March 1998); doi: 10.1117/12.304907
Show Author Affiliations
Samuel Peter Kozaitis, Florida Institute of Technology (United States)
Abdullah A. Basuhail, Florida Institute of Technology (Saudi Arabia)

Published in SPIE Proceedings Vol. 3391:
Wavelet Applications V
Harold H. Szu, Editor(s)

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