Adaptive wavelet threshold selection using higher-order statistics for signal denoising

Samuel Peter Kozaitis; Abdullah A. Basuhail

doi:10.1117/12.304907

26 March 1998 Adaptive wavelet threshold selection using higher-order statistics for signal denoising

Samuel Peter Kozaitis, Abdullah A. Basuhail

Proceedings Volume 3391, Wavelet Applications V; (1998) https://doi.org/10.1117/12.304907
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

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.

Citation Download Citation

Samuel Peter Kozaitis and Abdullah A. Basuhail "Adaptive wavelet threshold selection using higher-order statistics for signal denoising", Proc. SPIE 3391, Wavelet Applications V, (26 March 1998); https://doi.org/10.1117/12.304907

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available