Adaptive Wavelet Thresholding Denoising Algorithm Based on White Noise Detection and 3σ Rule
Dai Gui-ping · Journal of Transcluction Technology · 2005
Threshold de-noising method based on wavelet transform is an efficient method to reduce the white noise in the digital signal.In this method,the determination of the threshold,the decomposition order and the threshold estimation model are three key problems that need to be solved.The characteristics of the wavelet coefficients of useful signal and white noise are analyzed.A new method is proposed to determine the decomposition order adaptively,and a novel method based on 3σ rule is brought forward to determine the threshold of wavelet space of each order.Furthermore,a proved threshold estimation model of wavelet coefficients is proposed,which combines qualities of hard-thresholding and soft-thresholding models.Simulation results show that the method proposed has good performance of de-noising,and is especially used to detect weak signal from strong noise.