Because of strong speckle noise in SAR image,the Chan-Vese model level set segmentation method produced a lot of false segmentation.Meanwhile,the level set had disadvantages of large amount of computation and slow segmentation velocity.Therefore,the paper added a new internal force term—distance regularized term,got an improved curve evolution model, based on the Chan-Vese model.we got an improved model of the curve evolution.the model avoided the periodic updates of leve set function and had a greater time step.thus the segmentation speed was speeded up,the anti-noise capability was enhanced. We tested the model by processing the synthetic image and real SAR images.by comparison,the improved model had a higher numerical accuracy and faster division speed. As for image with strong noise,used the enhanced LEE filter,can further improve the speed and effect of the segmentation model. The result show that improved Chan-Vese model can rapid and efficient completion of SAR image segmentation with high robustness.