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A Review of Classification Methods of Remote Sensing Imagery

JIA Kun1,2,LI Qiang-zi1*,TIAN Yi-chen1,WU Bing-fang11.Institute of Remote Sensing Applications,Chinese Academy of Sciences,Beijing 100101,China2.Graduate University of Chinese Academy of Sciences,Beijing 100049,China  
Remote sensing data classification is an important way of information extraction and a hot research topic of remote sensing technique.Classification method of remote sensing data is an important issue,and effective selection of appropriate classifier is especially significant for improving classification accuracy.Along with the development of remote sensing technique,traditional parametric classifier is difficult to meet accuracy requirement,leading to the rapid development of intelligent algorithm based non-parametric classifiers.Recently,combined classifiers become a new hot topic for its ability of utilizing complement information of single classifier.In the present paper,characters and advantages of different classifiers as well as the research prospect are analyzed.The paper provides a scientific reference for the development of remote sensing data classification technique.
【Fund】: 中国科学院知识创新工程重大项目(KSCX1-YW-09-1);; 国家自然科学基金项目(41071277);; 国家高技术研究发展(863计划)项目(2009AA12Z1462)资助
【CateGory Index】: TP751
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