Recognition method of multi-feature fusion based on D-S evidence theory in SAR image
TONG Tao1, YANG Guang1, LI Xin2, YE Yi1, WANG Shoubiao1
1. Department of Aerospace Intelligence, Aviation University of Air Force, Changchun 130022, China; 2. Department of Training, Aviation University of Air Force, Changchun 130022, China
Abstract：In view of the low accuracy of the single feature-based method for target recognition in SAR image, a multi-feature decision-making level fusion method based on SVM and D-S evidence theory was proposed.After a series of image processing, the texture feature, Hu invariant moments feature and peek feature were extracted from the target image. Then the targets were classified according to each type of features utilizing SVM, and the results were used as evidence to construct the basic probability assignment. Conclusively, D-S combination rule of evidence was used to achieve fusion, and final recognition results were given by classification thresholds. The method is used for recognizing three-class targets in MSTAR database, and the recognition rate arrives at 95.5%. Experimental result shows that the method is effective for SAR images target recognition.
童涛, 杨桄, 李昕, 叶怡, 王寿彪. 基于D-S证据理论的多特征融合SAR图像目标识别方法[J]. 国土资源遥感, 2013, 25(2): 37-41.
TONG Tao, YANG Guang, LI Xin, YE Yi, WANG Shoubiao. Recognition method of multi-feature fusion based on D-S evidence theory in SAR image. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(2): 37-41.
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2013, Vol. 25 
