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《Beijing Surveying and Mapping》 2018-10
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Integrating Texture Features in Polarimetric SAR Image Classification Using SVM

SHEN Lu;QUAN Yanan;YU Zhezhu;MA Hongyu;Changbai Mountain Academy of Sciences;Jilin Provincial Joint Key Laboratory of Changbai Mountain Biocoenosis &Biodiversity;Anshan Electric Survey and Design Institute;  
At present,the traditional polarimetric SAR image classification method based on target decomposition feature usually can not meet the user's need for accuracy,so it is necessary to improve classification accuracy.Texture features are important to improve objects' recognition,integrating target decomposition is helpful to increase the feature vector effect in classification,and improve the low precision of polarimetric SAR classification problems.Therefore,this paper presented a method of polarimetric SAR image classification based on texture feature.The experimental results showed that this method could improve the classification accuracy of all kinds of objects and overall accuracy in different feature vector integrating texture features.
【CateGory Index】: TN957.52
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