To solve the problem of poor identification effect of current sensor pattern noise (SPN) extraction model in compressed video source detection,an improved SPN extraction model based on multi-scale transform domain adaptive Wiener filtering and a weighted maximum likelihood estimation 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,and then the video frame is input into the dual-density and dual-tree complex wavelet transform adaptive Wiener filtering 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 ROC curve and Kappa statistical coefficient.