Research on Remote Sensing Image of Land Cover Classification Based on Multiple Classifier Combination

查看全文 作　　者：DAI [1,2]Lijun;LIU [1]Chuang

机构地区：[1]Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;[2]Graduate University of Chinese Academy of Sciences, Beijing 100101, China

出　　处：《Wuhan University Journal of Natural Sciences》索引2011年第16卷第4期,共6页

基　　金：Supported by the National Natural Science Foundation of China (70873117) 摘　　要：This paper proposed an algorithm in which the maximum probability and the weighted average strategy were used for the combination of member classifiers. Using parallel computing, we test the algorithm on a China-Brazil Earth Resources Satellite (CBERS) image for land cover classification. The results show that using three computers in parallel can reduce the classification time by 30%, as compared with using only one computer with a dual core processor. The accuracy of the final image is 93.34%, and Kappa is 0.92. Multiple classifier combination can enhance the precision of the image classification, and parallel computing can increase the speed of calculation so that it becomes possible to process remote sensing images with high efficiency and accuracy. 关键词：多重分类器联合分类并行计算

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Research on Remote Sensing Image of Land Cover Classification Based on Multiple Classifier Combination

参考文献(21)

引证文献(2)

耦合文献(11)

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