The Wiener filtering principle and characteristics of a Pulse Couple Neural Network(PCNN) model were analyzed and a wavelet adaptive denoising method based on the PCNN(W-PCNN-WD)was proposed according to a statistical model of speckle noise combined with a wavelet transform to improve the quality of ultrasound image. Firstly, the ultrasound image was performed a log conversion to transform the speckle noise to an additive noise. Then, the Wiener filtering was used to process the medical image to get the variance of the additive noise as the threshold of wavelet. Furthermore, the image was preprocessed by the wavelet transform and wavelet coefficients were recomposed appropriately by using the PCNN. Finally, the image was processed again by the wavelet inverter and the exponential transforms to get a denoising image. The result shows that the proposed filtering method is better than the other filtering methods, and the Peak Signal to Noise Ratio( PSNR) from the proposed method is higher 9 dB than that from the Wiener filtering when the noise variance is 0.01. The method can keep the edge details of the information on the basis of removing speckle noise, which improves the visual quality of images greatly.