Extraction of incident irradiance from LWIR hyperspectral imagery

Pierre Lahaie

doi:10.1117/12.2067480

13 October 2014 Extraction of incident irradiance from LWIR hyperspectral imagery

Pierre Lahaie

Proceedings Volume 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II; 92500Z (2014) https://doi.org/10.1117/12.2067480
Event: SPIE Security + Defence, 2014, Amsterdam, Netherlands

Abstract

The atmospheric correction of thermal hyperspectral imagery can be separated in two distinct processes: Atmospheric Compensation (AC) and Temperature and Emissivity separation (TES). TES requires for input at each pixel, the ground leaving radiance and the atmospheric downwelling irradiance, which are the outputs of the AC process. The extraction from imagery of the downwelling irradiance requires assumptions about some of the pixels’ nature, the sensor and the atmosphere. Another difficulty is that, often the sensor’s spectral response is not well characterized. To deal with this unknown, we defined a spectral mean operator that is used to filter the ground leaving radiance and a computation of the downwelling irradiance from MODTRAN. A user will select a number of pixels in the image for which the emissivity is assumed to be known. The emissivity of these pixels is assumed to be smooth and that the only spectrally fast varying variable in the downwelling irradiance. Using these assumptions we built an algorithm to estimate the downwelling irradiance. The algorithm is used on all the selected pixels. The estimated irradiance is the average on the spectral channels of the resulting computation. The algorithm performs well in simulation and results are shown for errors in the assumed emissivity and for errors in the atmospheric profiles. The sensor noise influences mainly the required number of pixels.

Citation Download Citation

Pierre Lahaie "Extraction of incident irradiance from LWIR hyperspectral imagery", Proc. SPIE 9250, Electro-Optical Remote Sensing, Photonic Technologies, and Applications VIII; and Military Applications in Hyperspectral Imaging and High Spatial Resolution Sensing II, 92500Z (13 October 2014); https://doi.org/10.1117/12.2067480

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KEYWORDS

Sensors

Signal to noise ratio

Atmospheric modeling

Hyperspectral imaging

Atmospheric sensing

Computer simulations

Atmospheric corrections

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