A segmentation algorithm was proposed by using Nonsubsampled Contourlet Transform (NSCT) and Gabor filter to extract characteristics of images respectively and using Pulse Coupled Neural Networks (PCNN) to enhance the target areas.Characteristic figures were constructed for the high and low frequencies of NSCT and corresponding characteristic figures were also constructed for the Gabor filters.All the characteristic figures were enhanced by PCNN. Then,the enhanced figures were integrated and segmented reasonably.Images in MSTAR SAR data library under different jamming intensities were selected for experiment.The results indicated that:Compared with the common algorithms such as FCM and the algorithm based on Markov random field,the proposed algorithm can realize more accurate segmentation for SAR images and has strong immunity from interferences.