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《Journal of Remote Sensing》 2013-01
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Fast N-FINDR algorithm for endmember extraction based on chi-square distribution

DING Haiyong1,2,SHI Wenzhong2 1.School of Remote Sensing,Nanjing University of Information Science and Technology,Nanjing 210044,China;2.Department of Land Surveying and Geo-informatics,The Hong Kong Polytechnic University,Hong Kong,China  
N-FINDR algorithm were employed for endmember extraction for decomposing the mixed pixels,which searches for each pixel from the dimension reduced feature space induced using principal component transformation or maximum noise factor transformation method.Due to the large search range for the endmembers,the efficiency of the N-FINDR algorithm is low.In this paper,we proposed the improved fast N-FINDR algorithm aiming to decrease the computation cost by providing a relative smaller search range,i.e.the candidate endmember set which was only a subset of the entire feature space.N-FINDR algorithm assumed that all the endmembers located at the vertexes of the simplex,which means that these pixels should be far away from the central part of all the pixels.Therefore,the percentile of chi-square distribution can be used to segment out these possible endmembers into a candidate set,which has much smaller size.The performance of the proposed algorithm has been verified using both synthetic and real hyperspectral data.Under the same endmember extraction precision,the modified N-FINDR algorithm has faster computation velocity and a higher overall efficiency.
【Fund】: 香港特别行政区科研基金(编号:276/08E);; 国土环境与灾害监测国家测绘局重点实验室开放基金(编号:LEDM2010B06)~~
【CateGory Index】: TP751
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