New approach of ECG denoising based on 1 D double density complex DWT and SBWT
ABSTRACT In this paper we propose a new ECG denoising approach based on the application of double density complex denoising method in the stationary bionic wavelet transform domain. This approach consists at the first step in applying the to the noisy ECG signal in order to obtain two noisy coefficients and The latter is an approximation coefficient and is a detail one. The latter is then denoised using Soft thresholding for obtaining a denoised coefficient, The double density complex denoising method is applied to and we obtain a denoised coefficient, The denoised ECG signal is finally obtained from the application of the inverse of the to and This proposed technique is evaluated and compared to the double density complex 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 and (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
Comput. methods Biomech. Biomed. Eng. Imaging Vis.