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A Nonlinear Spectral Unmixing Method for Abundance Retrieval of Mineral Mixtures

机译:用于丰富矿物混合物的非线性光谱解密方法

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Minerals are generally present as intimate mixtures. The spectra of intimate mixtures in visible-infrared are complex function of abundance, grain size, and optical constants et.al, making the linear spectral unmixing model inapplicable. In this paper, we presented a nonlinear unmixing method by combining Shkuratov model (SK99) and Hapke model (H81) to unmix the mineral mixtures. For obtaining the abundances of mineral endmembers, we built up a look-up table (LUT) in the following steps: First, the optical constants were derived by SK99 model and then single scattering albedos of endmembers were computed. Second, the approximation of multiple scattering was derived by the Chandrasekhar H-function. Finally, LUT was established using H81 model. The root-mean-square error (RMSE) was calculated to find the best match between the reflectance of mixtures and LUT. We used the laboratory mineral mixtures to verify the accuracy of abundance estimation. The results show that RMSEs are less than 1% and the absolute errors of abundance retrieval are within 5%. The presented method can retrieve mineral abundance effectively and rapidly. It can be a potential method applying for hyperspectral images of the earth and planetary.
机译:矿物质通常存在为亲密混合物。可见红外线密集混合物的光谱是丰富,晶粒尺寸和光学常数Et.Al的复杂功能,使线性光谱解密模型不适用。在本文中,我们通过将Shkuratov模型(SK99)和Hapke模型(H81)组合给矿物混合物来呈现非线性解密方法。为了获得矿物终点的丰富,我们建立了以下步骤的查找表(LUT):首先,通过SK99模型导出光学常数,然后计算终点的单个散射玻璃玻璃玻璃。其次,通过ChandraseKhar H函数来源多次散射的近似。最后,LUT是使用H81模型建立的。计算根均方误差(RMSE),以找到混合物和LUT的反射率之间的最佳匹配。我们使用实验室矿物混合物来验证丰富估计的准确性。结果表明,RMSE小于1%,丰富检索的绝对误差在5%范围内。所提出的方法可以有效且快速地检索矿物丰富。它可以是申请地球和行星的高光谱图像的潜在方法。

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