An Accurate Approach to Hyperspectral Mineral Identification Based on Naive Bayesian Classification Model
HE Jin-xin1, CHEN Sheng-bo2, WANG Yang3, WU Yan-fan3
1. College of Earth Sciences, Jilin University, Changchun 130061, China 2. College of Geo-exploration Science and Technology, Jilin University, Changchun 130061, China 3. College of Computer Science and Technology, Jilin University, Changchun 130012, China
Abstract：The spectral absorption features are very similar between some minerals, especially hydrothermal alteration minerals related to mineralization, and they are also influenced by other factors such as spectral mixture. As a result, many of the spectral identification approaches for the minerals with similar spectral absorption features are prone to confusion and misjudgment. Therefore, to solve the phenomenon of “same mineral has different spectrums, and same spectrum belongs to different minerals”, this paper proposes an accurate approach to hyperspectral mineral identification based on naive bayesian classification model. By testing and analyzing muscovite and kaolinite, the two typical alteration minerals, and comparing this approach with spectral angle matching, binary encoding and spectral feature fitting, the three popular spectral identification approaches, the results show that this approach can make more obvious differences among different minerals having similar spectrums, and has higher classification accuracy, since it is based on the position of absorption feature, absorption depth and the slope of continuum.
贺金鑫1，陈圣波2，王 阳3，吴艳繁3 . 一种基于朴素贝叶斯分类模型的高光谱矿物精确识别方法 [J]. 光谱学与光谱分析, 2014, 34(02): 505-509.
HE Jin-xin1, CHEN Sheng-bo2, WANG Yang3, WU Yan-fan3 . An Accurate Approach to Hyperspectral Mineral Identification Based on Naive Bayesian Classification Model . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(02): 505-509.
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