Journal of Systems Engineering and Electronics

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Geometric active contour based approach for segmentation of high-resolution spaceborne SAR images

Shaoming Zhang1, Fang He1, Yunling Zhang2,*, Jianmei Wang1, Xiao Mei1, and Tiantian Feng1   

  1. 1. College of Surveying, Mapping and Geo-Informatics, Tongji University, Shanghai 200092, China;
    2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
  • Online:2015-02-13 Published:2010-01-03


Segmentation is the key step in auto-interpretation of high-resolution spaceborne synthetic aperture radar (SAR) images. A novel method is proposed based on integrating the geometric active contour (GAC) and the support vector machine (SVM) models. First, the images are segmented by using SVM and textural statistics. A likelihood measurement for every pixel is derived by using the initial segmentation. The Chan-Vese model then is modified by adding two items: the likelihood and the distance between the initial segmentation and the evolving contour. Experimental results using real SAR images demonstrate the good performance of the proposed method compared to several classic GAC models.

Key words: image segmentation, synthetic aperture radar (SAR) imagery, support vector machine (SVM), geometric active contour (GAC)