Coupled Subspace-Based Atmospheric Compensation of LWIR Hyperspectral Data

This paper deals with atmospheric correction in hyperspectral data acquired in the long-wave infrared (LWIR) spectral range. Atmospheric compensation (AC) is approached from a new perspective in that it is reformulated as an estimation problem on a low-rank subspace. Specifically, a subspace-based m...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2019-08, Vol.57 (8), p.5224-5238
Main Authors: Acito, N., Diani, M., Corsini, G.
Format: Article
Language:English
Subjects:
Absorption
Algorithms
Atmospheric compensation (AC)
Atmospheric conditions
Atmospheric correction
Atmospheric modeling
Compensation
Computer simulation
Data acquisition
Data models
Estimating techniques
Estimation
Exploitation
Hyperspectral imaging
hyperspectral thermal images
Image analysis
Image processing
Ocean circulation
Parameter estimation
Radiance
Subspaces
Upwelling
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Summary:This paper deals with atmospheric correction in hyperspectral data acquired in the long-wave infrared (LWIR) spectral range. Atmospheric compensation (AC) is approached from a new perspective in that it is reformulated as an estimation problem on a low-rank subspace. Specifically, a subspace-based model is exploited to represent both the atmospheric transmittance and the upwelling radiance. Taking into account the inherent correlation between these two quantities, we adopt a subspace model that constrains them to vary in a physically consistent way. Exploiting such a model, AC is formulated as a nonlinear least-squares estimation problem. An automatic procedure is proposed to estimate the unknown parameters, which is based only on the image analysis and does not need any atmospheric measurements. Results of an extensive experimental analysis carried out on simulated data are used to discuss the performance of the algorithm with respect to different atmospheric conditions. Finally, experimental evidence over a real LWIR hyperspectral image is provided.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2019.2897498