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.