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Atmospheric correction of hyperspectral images using qualitative information about registered scene
Author(s): Anna Denisova; Vladislav Myasnikov
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Paper Abstract

In paper a method of atmospheric correction of hyperspectral images is proposed. On the first stage, observed image is used to obtain parameters of atmospheric distortions using common radiative transfer model. In contrast to other existing approaches we use full nonlinear form of the radiative transfer model and linear spectral model, which is applied to describe undistorted hyperspectral pixels. The combination of both models allows us to evaluate parameters of atmospheric distortions using only hyperspectral image and qualitative information about the scene. The latter is a list of spectral signatories (undistorted), which can appear in different linear combinations in the registered scene. The proposed method does not require any precedential information (sets of pixels containing predefined information) or pure hyperspectral pixels. Thus, it can be applied for blind identification of the atmospheric distortion model and for further atmospheric correction. Experimental results presented in this paper demonstrate performance of the method.

Paper Details

Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034125 (17 March 2017); doi: 10.1117/12.2268511
Show Author Affiliations
Anna Denisova, Samara National Research Univ. (Russian Federation)
Vladislav Myasnikov, Samara National Research Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

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