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An iterative least squares approach to decorrelate minerals and ices contributions in hyperspectral images: Application to Cuprite (earth) and Mars

机译:迭代最小二乘探讨探讨矿物质和冰谱图像中的贡献:铜矿(地球)和火星的应用

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We present an Iterative Linear Spectral Unmixing Model (ILSUM) which is aimed at finding the main surface components that contribute to the signal in visible and infrared hyperspectral images. We processed the global dataset of the OMEGA imaging spectrometer onboard Mars Express up to orbit 5300, covering two martian years. We also present a preliminary test on AVIRIS data on the Cuprite (Nevada) site. We use ILSUM to identify the contribution of each endmember of an input library containing laboratory spectra of ices and mineral powders that are representative of the main mineral families. Synthetic spectra (pure slope endmembers) are included to account at first order for aerosol and grain size variations. Applied to the global OMEGA data set, this algorithm provides a distribution map for the main minerals present on the martian surface, which appears to be mainly dominated by pyroxenes, olivine, ferric oxides, with localized exposures of sulfates and phyllosilicates.
机译:我们提出了一种迭代线性光谱解密模型(ILSUM),其旨在找到有助于可见光和红外光谱图像中的信号的主表面分量。我们处理了Omega成像光谱仪的全球数据集,船上MARS表达到轨道5300,覆盖了两个火星岁月。我们还对Cuprite(内华达州)网站的Aviris数据初步测试。我们使用ILSUM来确定输入库的每个末端的贡献,其中包含代表主要矿物家庭的冰和矿物粉末的实验室谱。包括综合谱(纯斜率终端)以首先算用于气溶胶和晶粒尺寸变化的顺序。应用于全局欧米茄数据集,该算法为火星表面上存在的主要矿物质的分布图提供了主要矿物质,其主要由辉芬,橄榄石,氧化铁,硫酸盐和神经碱的局部暴露主导地位。

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