A Translation-Invariant Wavelet Denoising Method Based on Improved Threshold

By analyzing the soft threshold and hard threshold,a translation-invariant wavelet denoising method based on improved-threshold is proposed.In order to remove the interference between discontinuous points,the original signal is shifted circulatingly and repeatedly,and then the shifted signals are decomposed by wavelet separately.Afterwards, using the improved threshold quantization algorithm,the wavelet coefficients are estimated by processing the power of the wavelet coefficients and the power of the threshold,and then the signal is reconstructed.The reconstructed signals are shifted reversely,and then the denoised signal is obtained by averaging the reversely-shifted signals.Experimental results of the sEMG(surface electromyography) show that comparing with the traditional threshold methods,this method improves the SNR(signal noise ratio) and reduces the mean square error.