26 March 1998 Adaptive wavelet threshold selection using higher-order statistics for signal denoising
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel Peter Kozaitis, Samuel Peter Kozaitis, Abdullah A. Basuhail, Abdullah A. Basuhail, } "Adaptive wavelet threshold selection using higher-order statistics for signal denoising", Proc. SPIE 3391, Wavelet Applications V, (26 March 1998); doi: 10.1117/12.304907; https://doi.org/10.1117/12.304907

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