To solve the problem of poor identification effect of current sensor p attern noise (SPN) extraction model in compressed video source detection,an improved SPN extraction m odel based on multi-scale transform domain adaptive Wiener filtering and a weighted maximum likelihood est imation is proposed.Firstly,the video coding and decoding is interfered, the video frame is extracted in front of the loop filter module of the coder,an d then the video frame is input into the dual-density and dual-tree complex wavelet transform adaptive Wiener filte ring model to extract the noise residual.Finally,the SPN is estimated from the noise residual by weighted maximum likelihood estimation.Test and comparison are completed on the public video source database VISION. The experimental results show that the proposed improved SPN extraction model performs better than the traditional SPN extraction algorithm on R OC curve and Kappa statistical coefficient.