Spectral clustering is a similarity-based clustering algorithm on graph theory.When the processed image is very huge,it is very difficult and time-consuming to compute affinity matrix and its eigenvalues and eigenvectors.Aiming at the characteristics of synthetic aperture radar(SAR) images,a two-stage image segmentation algorithm was proposed,in which watershed was used to produce over-segmentation and an improved spectral clustering algorithm was applied to perform final clustering.The new algorithm can not only reduce the noise in SAR images and keep their boundary very well but also is valuable to the application of higher demand for time.To verify the performance of the proposed algorithm,it was applied to segment SAR images,and better segmentation results were obtained.