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罗文斐1, 罗寿枚2, 张 兵3, 钟 亮1(1.中国科学院遥感应用研究所,北京 100101;2.华南师范大学地理科学学院,广州 510631;3.中国科学院对地观测与数字地球科学中心,北京 100080)

摘 要
Fuzzy Presentation for Endmember Spectral Variability in Remote Sensing

LUO Wenfei1, LUO Shoumei2, ZHANG Bing3, ZHONG Liang1(1.Institute of Remote Sensing Applications Chinese Academy of Sciences,Beijing 100101;2.School of Geography Science,South China Normal University,Guangzhou 510631;3.Center for Earth Observation and Digital Earth,Chinese Academy of Sciences,Beijing 100080)

In remote sensing image,the event of mixed pixel can be presented by fuzzy extended probability measures.These measures are considered by fuzzy classification.However,due to the effect of nonlinear factor and the complexity of nature materials,spectral variability occurs to the endmembers,which leads to the primary error in the process of spectral unmixing.This paper focused on the fuzzy presentation on the endmember spectral variability by possibility distribution for remote sensing image: on the assumption of the multidimensional normal distribution,chi-square distribution is proposed for the fuzzy presentation.Based on the chi-square distribution,a possibility distribution fuzzy partition arithmetic is developed for fuzzy partition of endmembers in the whole image,which presents the endmember spectral variability.In order to evaluate the performance of the algorithm,an experiment using real hyperspectral image is demonstrated in this paper.The proposed algorithm clearly reveals the spectral variability of endmembers in the image,which provides valuable insight into the accuracy of mixed pixel analysis.