Skip to Main Content
A new synthetic aperture radar (SAR) image segmentation method based on a maximization of posterior marginals (MPM) algorithm with feature extraction and context model is proposed in this letter. First, Gabor wavelet and texture descriptor are used to extract features, which enhance intraclass similarities and interclass differences. Second, the number of regions within the same class is reduced in order to improve the reliability of the regional statistical characteristics. Finally, the MPM of each region combined with the context model is calculated by considering both the intralayer correlation and interlayer correlation. The experimental results show that the proposed method is efficient and effective for SAR image segmentation.