Aiming at the characteristics of Synthetic Aperture Radar (SAR) images and the problem of the standard graph cut segmentation algorithm's high computational complexity, a method of strong scattering objects segmentation based on graph cut and Mean Shift algorithm was proposed. Firstly, the image was pre-processed with the Mean Shift algorithm to produce over-segmentation areas. Then, a graph was built with nodes responding to over-segmentation areas, and then the results of SAR strong scattering targets segmentation were obtained by using graph cut algorithm. Compared with nodes responding to pixels in the standard graph cut algorithm, the number of nodes and edges in the graph were reduced by two orders of magnitude and the computational efficiency was significantly improved. Furthermore, according to the strong scattering characteristics of the targets in SAR images, the “object” terminal and the “background” terminal were defined automatically to reduce human interaction. The experiments show that the proposed method combines the advantages of Mean Shift and graph cut effectively, and it can effectively extract SAR strong scattering targets from the background clutter.