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Interpretation of hyperspectral remote-sensing imagery by spectrum matching and look-up tables

机译：通过光谱匹配和查询表解释高光谱遥感影像

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摘要

A spectrum-matching and look-up-table (LUT) methodology has been developed and evaluated to extract environmental information from remotely sensed hyperspectral imagery. The LUT methodology works as follows. First, a database of remote-sensing reflectance (R_(rs)) spectra corresponding to various water depths, bottom reflectance spectra, and water-column inherent optical properties (IOPs) is constructed using a special version of the HydroLight radiative transfer numerical model. Second, the measured R_(rs) spectrum for a particular image pixel is compared with each spectrum in the database, and the closest match to the image spectrum is found using a least-squares minimization. The environmental conditions in nature are then assumed to be the same as the input conditions that generated the closest matching HydroLight-generated database spectrum. The LUT methodology has been evaluated by application to an Ocean Portable Hyperspectral Imaging Low-Light Spectrometer image acquired near Lee Stocking Island, Bahamas, on 17 May 2000. The LUT-retrieved bottom depths were on average within 5% and 0.5 m of independently obtained acoustic depths. The LUT-retrieved bottom classification was in qualitative agreement with diver and video spot classification of bottom types, and the LUT-retrieved IOPs were consistent with IOPs measured at nearby times and locations.
机译：已经开发并评估了光谱匹配和查找表（LUT）方法，以从遥感高光谱图像中提取环境信息。 LUT方法的工作原理如下。首先，使用特殊版本的HydroLight辐射传递数值模型，构建与各种水深，底部反射光谱和水柱固有光学特性（IOP）相对应的遥感反射光谱（R_（rs））的数据库。其次，将针对特定图像像素的测量R_（rs）光谱与数据库中的每个光谱进行比较，并使用最小二乘最小化找到与图像光谱最接近的匹配。然后假定自然界中的环境条件与生成最接近由HydroLight生成的数据库光谱的输入条件相同。通过将LUT方法应用于2000年5月17日在巴哈马的Lee Stocking岛附近获取的海洋便携式高光谱成像低光谱仪图像进行评估。LUT挖出的底部深度平均在独立获得的5％和0.5 m以内声学深度。 LUT检索的底部分类与潜水员和视频点对底部类型的分类在质量上一致，LUT检索的IOP与在附近时间和位置测量的IOP一致。

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