基于双树复小波变换信号去噪算法研究

离散小波变换被广泛应用于数字信号的去噪处理中，特别是非平稳信号、瞬时时变信号等的去噪，但是有平移敏感性的缺陷。为了克服这种缺陷，文中采用双树复小波变换进行信号去噪，并使用硬阈值、软阈值等准则进行滤波处理。最后采用SNR（信噪比）和MSE（均方误差）来评估两者信号去噪效果。结果表明，双树复小波变换能够较好的保存信号的细节信息，其去噪效果优于离散小波变换。

Signal denoising algorithm based on double tree complex wavelet transform

Discrete wavelet transform is widely used in denoising of digital signals, especially nonstationary signals, instantaneous time varying signals, but it has the drawbacks of translational sensitivity. In order to overcome the shortcomings of discrete wavelet transform, the paper used the double tree complex wavelet transform to denoise the signal, and used the hard threshold, soft threshold and other criteria to filter the signal. Finally, SNR (signal to noise ratio) and MSE(mean square error) were used to evaluate the effects of signal denoising. The results show that the double wavelet complex wavelet transform which saves the details of the information of the signal is better than discrete wavelet transform in denosing the signal.