In order to improve the visual effects of the medical image and improve image clarity,a targeted image enhancement system for medical images is designed. For the electronic noise of CT images,a wavelet packet denoising algorithm based on amendments Wiener filtering is proposed; For speckle noise of B-mode ultrasound image,a wavelet adaptive speckle reduction algorithm based on the pulse coupled neural network (PCNN)model is proposed. For medical images with low contrast and blur edge,a wavelet-based medical image enhancement algorithm is proposed. The peak signal to noise ratio (PSNR)from the PCNN method is 9dB higher than that from the Wiener filtering when the noise variance is 0.01. Noise points can be quickly found,and fixed point denoising is carried out,the medical image contrast can be effectively improved,edge details are enhanced,the location of the lesion point is highlighted. It provides a more clear and accurate basis for symptoms observing of health workers.