New approach of ECG denoising based on 1-D double-density complex DWT and SBWT

摘要

In this paper we propose a new ECG denoising approach based on the application of 1 - D double-density complex DWT denoising method in the stationary bionic wavelet transform (SBWT) domain. This approach consists at the first step in applying the SBWT to the noisy ECG signal in order to obtain two noisy coefficients wtb1 and wtb2. The latter is an approximation coefficient and wtb1is a detail one. The latter is then denoised using Soft thresholding for obtaining a denoised coefficient, wtd1. The 1 - D double-density complex DWT denoising method is applied to wtb2 and we obtain a denoised coefficient, wtd2. The denoised ECG signal is finally obtained from the application of the inverse of the SBWT, SBWT~(-1) to wtd1 and wtd2. This proposed technique is evaluated and compared to the 1 - D double-density complex DWT denoising one, the denoising technique based on Wavelets and Hidden Markov Models, the technique based on Non-Local Means and our previous proposed approach based on BWT and FWT_TI (translation invariant forward wavelet transform). The simulation results obtained from the computations of SNR (ratio), MAE (mean absolute error), PSNR (peak SNR) and CC (cross-correlation), show that the proposed technique outperforms the other techniques used in our evaluation.