基于实测高光谱数据的矿物含量提取方法研究

A Method to Extract Content of Minerals Based on Measured Hyperspectral Data

针对利用线性模型提取矿物含量精度较低的问题,以波长范围为350-2 500nm的岩石光谱为数据源,基于光谱匹配方法进行矿物识别,应用简化的Hapke模型将岩石样品反射率转换为单次反照率,利用线性模型分解单次反照率进行含量提取,并通过分段滤波及建立区域光谱库的方法提高识别精度,建立了一种基于实测光谱数据的矿物含量提取方法。通过对包古图V号岩体光谱数据的分析,与X射线衍射结果相比,该方法对长石类矿物的识别精度为100%,含量提取精度为80.5%;对粘土类蚀变矿物的识别精度为92.2%,含量提取的精度为92.36%。该方法将矿物学共生关系加入到矿物识别方法中,保证了结果的可靠性;提出了分段滤波的预处理思路,避免了滤波算法对光谱波形及吸收特征的影响,并且据有较好的去噪效果;应用Hapke模型进行实测的岩石光谱解混,能避免复杂的光谱非线性分解计算,从理论上提高矿物含量提取的精度和计算的效率。该方法对快速分析蚀变信息等工作具有一定的指导意义。

To improve the accuracy of mineral content extraction by linear decomposition model,a method was established,which took rock spectra with wavelength from 350 to 2 500 nm as the data source,identified minerals based on spectral matching methods,applied Hapke model to transform spectral reflectance into single scattering albedo and resolved single scattering albedo to get mineral content.In this method,sectional noise filtering and regional mineral spectra library were added to improve the identifying accuracy.Based on the analysis on the fifth Baogutu rock body,compared with XRD results,accuracies of quartz,feldspar class and altered minerals identification were 75%,100% and 92.2% separately.Accuracy of the content extraction of feldspar class,hornblende and altered minerals were 80.5%,64%,92.36% separately.This method added mineralogy symbiotic relationship into mineral identification to ensure the reliability,proposed the idea of sectional noise filtering to avoid the influence of filtering algorithm,applied the single scattering albedo to avoid the complex nonlinearly calculations to improve the accuracy theoretically.This method has a certain guiding significance for the work such as rapid analysis of alteration information.