The invention discloses a level set SAR (Synthetic Aperture Radar) image segmentation method by combining edges and a regional probability density difference, belonging to the technical field of image processing and mainly solving the problems of difficult segmentation of SAR images with fuzzy edges and inaccurate positioning to real edges of the SAR images, of the traditional level set method. The method comprises the following implementation steps of: firstly, detecting an edge intensity modulus absolute value of Rmax of an SAR image by applying an ROEW operator; secondly, initializing a level set function phi, segmenting the SAR image into an inner region omega1 and an outer region omega2, and solving for the intensity mean values c1 and c2 of the two regions; thirdly, solving for the estimated probability densities of the two regions omega1 and omega2 according to c1 and c2 and calculating the actual probability densities p1 and p2 of the two regions; and fourthly, constructing a total energy function ESAR, solving for a gradient downstream equation by applying a variational method, and updating the level set phi to obtain new segmentation regions omega1 and omega2. Indicated by experimental results, the segmentation method can be used for obtaining more ideal segmentation effect and be used for the edge detection and the target identification of the SAR images.