The present study of Extracorporeal Shock Wave Lithotripsy (ESWL) system focuses on the topic of energy emission, but there are less optimization research on the information acquisition. To achieve the goal of stone fragmentation without any damage to the human body, efficient data acquisition in ESWL images is an important research subject. For processing information of medical treatment activity, based on the statistical distribution of image pixels, adaptive wavelet lifting schemes were applied to different image regions using a adaptive selector, by which noise suppression was fulfilled while key features of the human body were retained. To achieve minimal mean square error, bivariate soft thresholding was provided here. This study provided more accurate, intelligent data, and clinical decision support ability for medical personnels. The experimental results demonstrate the proposed method is of low complexity in its implementation time and generates minimal reconstruction error approaching that of the classical wavelets. Moreover, this algorithm outperforms the existing methods in terms of quantitative performance measures as well as clinical observations.