New Method for Improving the Performance of SAR Image Segmentation
Yan Xue-ying Jiao Li-cheng Wang Ling-xia Wan Hong-lin
The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education,Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, China
Abstract:Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This method compresses the redundant GLCP features extracted by the adaptive window Gabor filtering in different direction coefficient blocks using compressed sensing, then the Fuzzy C-Mean (FCM) clustering method is utilized to complete the clustering and obtain the segmentation result. The experiment results show that the new method has advantages in the edge preservation and direction extraction, and obtains better segmentation results with respect to other methods.
颜学颖, 焦李成, 王凌霞, 万红林. 一种提高SAR图像分割性能的新方法[J]. 电子与信息学报, 2011, 33(7): 1700-1705.
Yan Xue-Ying, Jiao Li-Cheng, Wang Ling-Xia, Wan Hong-Lin. New Method for Improving the Performance of SAR Image Segmentation. , 2011, 33(7): 1700-1705.