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| 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 |
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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.
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Received: 04 November 2010
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Corresponding Authors:
Yan Xue-ying
E-mail: xueyingyanyxy@gmail.com
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2011, Vol. 33 
