Research on ECG signal denoising based on dual-tree complex wavelet transform

In ECG signal processing, in order to avoid the phenomena of Gibbs oscillation and severe frequency aliasing, a new ECG signal denoising algorithm is presented, which is based on dual-tree complex wavelet transform and combined with the maximum a posteriori estimation to determine the threshold. The signal-to-noise ratio and mean square error are used to evaluate the denoising effects of the dual-tree complex wavelet transform and discrete wavelet transform. The experimental result shows that compared with traditional discrete wavelet transform, the dual-tree complex wavelet transform reduces noise more thoroughly and retains boundary and texture characteristics better. The dual-tree complex wavelet transform can be used as a new denoising method for biomedical signal denoising processing.