Abstract
Terrain categorization and target detection algorithms applied to Hyperspectral Imagery (HSI) typically operate on the measured reflectance (of sun and sky illumination) by an object or scene. Since the reflectance is a non-dimensional ratio, the reflectance by an object is nominally not affedted by variations in lighting conditions. Atmospheric Correction (also referred to as Atmospheric Compensation, Characterization, etc.) Algorithms (ACAs) are used in application of remotely sensed HSI datat to correct for the effects of atmospheric propagation on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is an ACA created for HSI applications in the visible through shortwave infrared (Vis-SWIR) spectral regime. FLAASH derives its physics-based mathematics from MODTRAN4.
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