MPM SAR Image Segmentation Using Feature Extraction and Context Model

作者：Hou, Biao^*; Zhang, Xiangrong; Li, Nan

来源：IEEE Geoscience and Remote Sensing Letters, 2012, 9(6): 1041-1045.

DOI：10.1109/LGRS.2012.2189352

• Hierarchical Markov random field model
• maximization of posterior marginals (MPM)
• SAR image segmentation
• synthetic aperture radar (SAR)
• watershed segmentation

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.

• 出版日期2012-11
• 单位西安电子科技大学