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《Science of Surveying and Mapping》 2016-01
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Change detection of multi-temporal remote sensing images using minimum cross-entropy

HUANG Kefeng;YU Xueqin;HUANG Liang;Kunming Surveying and Mapping Institute;Faculty of Land Resource Engineering,Kunming University of Science and Technology;  
Aiming at the insufficiency of efficient determination on the change threshold in multi-temporal remote sensing image change detection,the paper proposed an algorithm based on minimum cross-entropy:first,the noise in bi-temporal remote sensing images was eliminated respectively by median filtering method;and the ratio method merged with the difference method was used to obtain the difference image for the multi-temporal remote sensing image;then the best change threshold of the difference image was determined by minimum cross entropy method,and the difference image was segmented to obtain the change regions;finally,the accuracy of change detection was evaluated.Experimental result showed the feasibility of the method with high precision.
【Fund】: 云南省教育厅科学研究基金项目(2013J062);; 云南省博士研究生学术新人奖支持项目
【CateGory Index】: P237
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Chinese Journal Full-text Database 1 Hits
1 DU Peijun1,2,LIU Sicong2 1.Department of Geographic Information Science,Nanjing University,Nanjing 210093,China; 2.Key Laboratory for Land Environment and Disaster Monitoring,State Bureau of Surveying and Mapping of China, China University of Mining and Technology,Xuzhou 221116,China;Change detection from multi-temporal remote sensing images by integrating multiple features[J];Journal of Remote Sensing;2012-04
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1 JIAN Can-liang;ZHAO Bin-bin;DENG Min;YU Li-yu;State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing,Wuhan University;Department of Geo-informatics,Central South University;Fujian Provincial Geomatics Center;;An Approach to Change Detection by Comparison of Corresponding Objects in Multi-scale Maps[J];Geography and Geo-Information Science;2013-05
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