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《Acta Scientiarum Naturalium Universitatis Pekinensis》 2008-06
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Blind Separation of Component Information from Hyperspectral Data

TAO Xin,FAN Wenjie ,XU XiruInstitute of RS and GIS of Peking University,Beijing 100871  
Blind signal separation(BSS)based on the technique of independent component analysis(ICA)was introduced to the quantitative remote sensing field for mixed pixel unmixing.The scale invariant problem of the classical method was solved and the spectral and weight information of components was synchronously gained from hyperspectral data.The algorithm was further improved in the computer numerical simulation experiments,where the method for choosing best spectral coverage for retrieval was presented.Its robustness was also discussed.It was finally applied on the HYPERION hyperspectral image of the study area in Hengshan county,Shanxi Province,for retrieving the vegetation cover in pixels.The accuracy validation by using SPOT5 image shows the high accuracy of this algorithm.
【Fund】: 国家自然科学基金(40401036);; 国家“863”计划(2005AA133011XZ07)资助项目
【CateGory Index】: TP751
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