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《Remote Sensing Technology and Application》 2012-05
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Comparative Analysis between Two Sub-pixel Mapping Methods based on Spatial Correlation Characteristics

Chen Yuehong1,2,Ge Yong1(1.State Key Laboratory of Resources and Environment Information Systems,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China; 2.Graduate University of Chinese Academy of Sciences,Beijing 100049,China)  
Compared two sub-pixel mapping methods which are based on the spatial correlation characteristics.One method is based on Hopfield Neural Network(HNN) and the other is based on geometric theory.A study with TM imagery data is employed to evaluate the performance measured by accuracy,visual effects and time consuming on the two methods.The comparisons illustrate that the availability of the spatial correlation incorporated into the two means is perfectely expressed in the results,and five conclusions are provided for the sequential researches of sub-pixel mapping as well.
【Fund】: 国家自然科学基金项目(40971222);; 中国科学院地理科学与资源研究所自主部署创新项目(201003009)资助
【CateGory Index】: TP751
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【Co-citations】
Chinese Journal Full-text Database 2 Hits
1 Lin Haobo1),2),Bo Yanchen1),Wang Jindi1),Song Danxia1) 1)(Research Center for Remote Sensing and GIS,School of Geography,Beijing Normal University;State key Laboratory of Remote Sensing Science,Beijing 100875 China)2)(Computing Center,Hebei University,Baoding 071000 China);Research progress in super-resolution mapping from remotely sensed imagery[J];Journal of Image and Graphics;2011-04
2 Ling Feng1),Wu Shengjun1),Xiao Fei1),Wu Ke2),Li Xiaodong1) 1)(Institute of Geodesy and Geophysics,Chinese Academy of Sciences,Wuhan 430077 China) 2)(China University of Geosciences,Wuhan 430074 China);Sub-pixel mapping of remotely sensed imagery:a review[J];Journal of Image and Graphics;2011-08
【Secondary Citations】
Chinese Journal Full-text Database 1 Hits
1 YI Chang,PAN Yao-zhong,ZHANG Jin-shui(Key Laboratory of Environmental Change and Natural Disaster,Ministry of Education of China,College of Resources Science & Technology,Beijing Normal University,Beijing 100875,China);Research on Super-resolution Mapping for Remote Sensing Images Based on a Multi-scale Spatial ANN-CA Model[J];Geography and Geo-Information Science;2007-03
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