文献类型：会议论文

英文题名：Feature selection method of support vector machinefor polarimetricsar landcover classification

作者：Feng, Qi[1] Chen, Er-Xue[1] Li, Zengyuan[1] Guo, Ying[1] Li, Wenmei[1]

第一作者：Feng, Qi

机构：[1] Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China

会议论文集：Proceedings of Dragon 2 Final Results and Dragon 3 Kick-Off Symposium

会议日期：June 25, 2012 - June 29, 2012

会议地点：Beijing, China

语种：英文

外文关键词：Image enhancement - Support vector machines - Synthetic aperture radar

年份：2013

摘要：In order to improve feature selection method based on SVM, we use quad- polarization Radarsat-2 SAR images as experimental data. The first disadvantage need to be improved is feature search method, the exhaust algorithm is used to get the most comprehensive feature combination. Another disadvantage need to be improved is the evaluation criterions for features, some testing samples are used to validate the classifier to evaluate the features more precisely. The results indicate that, the higher accuracy is obtained by the feature selection method developed in this paper than by the feature selection method based on knowledge and the non-feature selection method. The accuracies of these three method are 84.96%, 75.74% and 65.68%.