In order to sovle the problem of expensive cost and the interference of cross terms in two-dimensional (2D) Wigner-Ville distribution (WVD) category, a novel target and target shadow segmentation method of synthetic aperture radar (SAR) images based on the two-dimensional Pseudo Wigner-Ville distribution (PWVD) decomposition were proposed. Firstly, 2D local energy maps of every pixel of original SAR image were obtained through local 2D-PWVD transform to SAR image. Then, the resultant data which are 2D local energy maps of every pixel of original SAR image could be arranged as N energy maps which are the same size with original SAR image. Finally, the different processing methods to the resultant data in frequency dimension were adopted according to different energy maps. The marker region image of target and target shadow was formed through adding the filtered energy maps.The segmentation experiment for MSTAR chips were taken using the proposed method.The comparisons between segmentation images of our method and segmentation images of the algorithm based on distance or azimuth of max energy, and between segmentation images of our method and segmentation images of the compounding segmentation algorithm based on two-parameter CFAR and Markov Random Field were carried out. The results show that the segmentation images by the presented algorithm preserve the abundant detail information of original images.