Spectral reflectance separation using physics-based constraints on atmospheric and illumination functions in frequent revisit hyperspectral data

Glenn Healey; Weishi Li

doi:10.1117/12.2677557

20 October 2023 Spectral reflectance separation using physics-based constraints on atmospheric and illumination functions in frequent revisit hyperspectral data

Glenn Healey, Weishi Li

Author Affiliations +

Proceedings Volume 12688, Imaging Spectrometry XXVI: Applications, Sensors, and Processing; 1268807 (2023) https://doi.org/10.1117/12.2677557
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

We present a method for separating the effects of the illumination and atmosphere from spectral reflectance in visible through short-wave infrared (VNIR/SWIR) hyperspectral images collected several times per hour. The data is collected from a tower-based sensor which operates over a 360 degree field-of-view which includes many atmospheric paths in off-nadir viewing geometries. The frequency of collection allows physics-based atmospheric perturbation models to be exploited to constrain the degree of variation in the atmospheric spectral functions. The method makes use of distinctive structure in atmospheric and reflectance spectra that is uncovered using a large MODTRAN atmospheric database. The method is evaluated over a set of hyperspectral data acquired for a region of southern California. We show that this approach can be used to accurately separate spectral reflectance and the illumination/atmospheric conditions in frequent revisit VNIR/SWIR hyperspectral images.

Citation Download Citation

Glenn Healey and Weishi Li "Spectral reflectance separation using physics-based constraints on atmospheric and illumination functions in frequent revisit hyperspectral data", Proc. SPIE 12688, Imaging Spectrometry XXVI: Applications, Sensors, and Processing, 1268807 (20 October 2023); https://doi.org/10.1117/12.2677557

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