Title :
Wavelet thresholding using higher-order statistics for signal denoising
Author :
Zhang, W. ; Zhao, X.H.
Author_Institution :
Coll. of Telecommun. Eng., Jilin Univ., Changchun, China
Abstract :
The paper demonstrates a higher-order statistics (HOS) based method of wavelet thresholding for signal denoising. We calculate the triple correlation coefficients of wavelet-signal correlation for identification of wavelet coefficients uncorrupted by noise. Since the higher than second-order moments of the Gaussian probability function are zero, the Gaussian noise can be eliminated completely. The method is also valid for unknown spectral density noise. The results of computer simulation show the availability and the effectiveness of the proposed wavelet thresholding method
Keywords :
Gaussian distribution; Gaussian noise; higher order statistics; identification; signal processing; wavelet transforms; Gaussian noise elimination; Gaussian probability function; HOS; computer simulation; higher-order statistics; identification; second-order moments; signal denoising; triple correlation coefficients; unknown spectral density noise; wavelet thresholding; Availability; Computer simulation; Educational institutions; Gaussian noise; Higher order statistics; Noise reduction; Probability; Signal denoising; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
Conference_Location :
Beijing
Print_ISBN :
0-7803-7010-4
DOI :
10.1109/ICII.2001.983679
