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比值导数法矿物组分光谱解混模型研究
引用本文:赵恒谦,张立福,吴太夏,黄长平.比值导数法矿物组分光谱解混模型研究[J].光谱学与光谱分析,2013,33(1):172-176.
作者姓名:赵恒谦  张立福  吴太夏  黄长平
作者单位:1. 遥感科学国家重点实验室,中国科学院遥感应用研究所,北京 100101
2. 中国科学院大学,北京 100049
基金项目:国家自然科学基金项目(41072248, 41272364)和国家重点基础研究发展计划(2010CB434800)资助
摘    要:矿物丰度含量的精确分析是高光谱遥感技术定量分析中的难点。将化学领域的比值导数光谱算法进行总结,将其引入遥感反射率光谱分析,提出了基于线性光谱混合模型的比值导数光谱解混模型,并利用石膏和绿帘石粉末混合物进行了模型的精度分析。实验结果表明,矿物粉末混合物在不同波段其光谱混合特性有所不同,其中部分波段有较强的线性混合特征。采用部分强线性混合波段进行光谱解混,可以取得比全波段解混算法更好的结果。比值导数法光谱解混模型简洁,可以得到高精度的矿物成分反演结果,对于固定端元组成的混合光谱定量分析有较大潜力。

关 键 词:高光谱  光谱解混  比值导数法  线性光谱混合模型    
收稿时间:2012/6/6

Research on the Model of Spectral Unmixing for Minerals Based on Derivative of Ratio Spectroscopy
ZHAO Heng-qian,ZHANG Li-fu,WU Tai-xia,HUANG Chang-ping.Research on the Model of Spectral Unmixing for Minerals Based on Derivative of Ratio Spectroscopy[J].Spectroscopy and Spectral Analysis,2013,33(1):172-176.
Authors:ZHAO Heng-qian  ZHANG Li-fu  WU Tai-xia  HUANG Chang-ping
Institution:1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China2. University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:The precise analysis of mineral abundance is a key difficulty in hyperspectral remote sensing research. In the present paper, based on linear spectral mixture model, the derivative of ratio spectroscopy (DRS) was introduced for spectral unmixing of visible to short-wave infrared (Vis-SWIR; 0.4~2.5 μm) reflectance data. The mixtures of different proportions of plaster and allochite were analyzed to estimate the accuracy of the spectral unmixing model based on DRS. For the best 5 strong linear bands, the Pearson correlation coefficient (PCC) of the abundances and the actual abundances were higher than 99.9%, while the root mean square error (RMSE) is less than 2.2%. The result shows that the new spectral unmixing model based on DRS is simple, of rigorous mathematical proof, and highly precise. It has a great potential in high-precision quantitative analysis of spectral mixture with fixed endmembers.
Keywords:Hyperspectral  Spectral unmixing  Derivative of ratio spectroscopy  Linear mixture model
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