Atmospheric correction of hyperspectral images using qualitative information about registered scene

Anna Denisova; Vladislav Myasnikov

doi:10.1117/12.2268511

17 March 2017 Atmospheric correction of hyperspectral images using qualitative information about registered scene

Anna Denisova, Vladislav Myasnikov

Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034125 (2017) https://doi.org/10.1117/12.2268511
Event: Ninth International Conference on Machine Vision, 2016, Nice, France

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.

Citation Download Citation

Anna Denisova and Vladislav Myasnikov "Atmospheric correction of hyperspectral images using qualitative information about registered scene", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034125 (17 March 2017); https://doi.org/10.1117/12.2268511

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