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本文提出了一种光谱吸收鉴别模型，拟通过矿物光谱吸收特征的鉴别，在成象光谱上实现矿物直接识别与填图。该模型的核心是光谱吸收指数技术（ＳＡＩ）。从理论上探讨了ＳＡＩ的本质，应用Ｈａｐｋｅ光谱模型讨论了ＳＡＩ与光谱吸收系数（ｄ）以及单散射反照率（ｗ）之间的函数关系，并从成象光谱图象辐射信息传递过程分析了图象ＳＡＩ与光谱吸收深度的关系，而光谱吸收深度与岩石矿物成分含量之间具有定量关系，这显示了ＳＡＩ提取矿物定量遥感信息能力。ＳＡＩ已经成功地应用于ＦＩＭＳ、ＭＡＩＳ和ＧＥＲＩＳ图象处理与矿物填图，本文通过哈图、塔里木、以及澳大利亚松谷的实例研究，表明ＳＡＩ是一种有效的提取矿物类型与丰度信息的方法。
In this paper, a spectral absorption identification model is proposed, which is to identify the mineral absorption spectrum and identify and map the mineral directly on the imaging spectrum. The core of this model is the Spectral Absorption Index (SAI) technique. The essence of SAI is discussed theoretically. The relationship between SAI and spectral absorption coefficient (d) and single-scattering albedo (w) is discussed based on Hapke spectral model. From the information transmission process of imaging spectral image The relationship between the SAI of the image and the depth of spectral absorption, and the relationship between the spectral absorption depth and the content of rock mineral components, shows the capacity of SAI to extract mineral quantitative remote sensing information. SAI has been successfully applied to image processing and mineral mapping of FIMS, MAIS and GERIS. This paper, through the case studies of Hata, Tarim and Song Valley of Australia, shows that SAI is an effective method for extracting information on mineral types and abundances.