Multiscale modeling for classification of SAR imagery using hybrid EM algorithm and genetic algorithm

作     者：Xianbin Wen a,b, Hua Zhang a,b, Jianguang Zhang a,b, Xu Jiao a,b, Lei Wang a,b a Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300191, China b Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of Education, Tianjin 300191, China 

作者机构：Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin 300191 China 

出 版 物：《Progress in Natural Science:Materials International》 (自然科学进展·国际材料(英文))

年 卷 期：2009年第19卷第8期

页      面：1033-1036页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 12[管理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 0835[工学-软件工程] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 60872064 and60375003) the Natural Science Foundation of Tianjin(Grant Nos. 08JCYBJC12300 and 08JCYBJC12200) the Science Foundation of Tianjin University of Technol-ogy (2006BA15) 

主　　题：SAR imagery Classification Multiscale Hybrid EM algorithm Genetic algorithm 

摘      要：A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of synthetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR) model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.