A Method of Hyperspectral Quantificational Identification of Minerals Based on Infrared Spectral Artificial Immune Calculation
LIU Qing-jie1, 2, JING Lin-hai1, 2, LI Xin-wu1, 2, BI Jian-tao1, 2, WANG Meng-fei3, LIN Qi-zhong1, 2
1. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China 2. Key Laboratory of Digital Earth, Chinese Academy of Sciences, Beijing 100094, China 3. China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
Abstract：Rapid identification of minerals based on near infrared (NIR) and shortwave infrared (SWIR) hyperspectra is vital to remote sensing mine exploration, remote sensing minerals mapping and field geological documentation of drill core, and have leaded to many identification methods including spectral angle mapping (SAM), spectral distance mapping(SDM), spectral feature fitting(SFF), linear spectral mixture model(LSMM), mathematical combination feature spectral linear inversion model(CFSLIM) etc. However, limitations of these methods affect their actual applications. The present paper firstly gives a unified minerals components spectral inversion (MCSI) model based on target sample spectrum and standard endmember spectral library evaluated by spectral similarity indexes. Then taking LSMM and SAM evaluation index for example, a specific formulation of unified MCSI model is presented in the form of a kind of combinatorial optimization. And then, an artificial immune colonial selection algorithm is used for solving minerals feature spectral linear inversion model optimization problem, which is named ICSFSLIM. Finally, an experiment was performed to use ICSFSLIM and CFSLIM to identify the contained minerals of 22 rock samples selected in Baogutu in Xinjiang China. The mean value of correctness and validness identification of ICSFSLIM are 34.22% and 54.08% respectively, which is better than that of CFSLIM 31.97% and 37.38%; the correctness and validness variance of ICSFSLIM are 0.11 and 0.13 smaller than that of CFSLIM, 0.15 and 0.25, indicating better identification stability.
刘庆杰1, 2，荆林海1, 2，李新武1, 2，毕建涛1, 2，王梦飞3，蔺启忠1，2 . 一种红外光谱免疫计算的矿物组分定量提取方法 [J]. 光谱学与光谱分析, 2013, 33(04): 954-958.
LIU Qing-jie1, 2, JING Lin-hai1, 2, LI Xin-wu1, 2, BI Jian-tao1, 2, WANG Meng-fei3, LIN Qi-zhong1, 2 . A Method of Hyperspectral Quantificational Identification of Minerals Based on Infrared Spectral Artificial Immune Calculation . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(04): 954-958.
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