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Computer Optics, 2016, Volume 40, Issue 4, Pages 526–534 (Mi co247)  

IMAGE PROCESSING, PATTERN RECOGNITION

Atmospheric correction of hyperspectral images using small volume of the verified data

A. Yu. Denisovaab, V. V. Myasnikovab

a Samara National Research University, Samara, Russia
b Image Processing Systems Institute îf RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

Abstract: In this article, we propose a novel method for atmospheric correction of hyperspectral imagery. At the first stage, the atmospheric correction parameters are derived from a scene image using a well-known radiation transfer model. In contrast to the other methods, we apply the standard equation of radiation transfer in a nonlinear form to describe atmospheric effects and a linear spectral mixture model to describe the unknown undistorted hyperspectral image. Applying both of these mathematical models simultaneously, we estimate the parameters of atmospheric correction using the hyperspectral image itself and the verified data about the registered scene. The verified data is taken to mean a set of (undistorted) spectral signatures, which can be presented in different linear combinations in the registered scene. Neither precedential information (a set of pixels containing predefined spectral signatures) nor pure hyperspectral pixels are required in our method. Therefore, the proposed method can be applied for the identification of a model of atmospheric distortions and their subsequent correction. The experimental results presented in the article demonstrate qualitative characteristics of the proposed method.

Keywords: Earth remote sensing, radiation transfer equation, hyperspectral images, spectral signatures, spectral profile, linear spectral model.

Funding Agency Grant Number
Russian Science Foundation 14-31-00014
Russian Foundation for Basic Research 16-37-00043_ìîë_à
15-07-01164-à
This work was supported in part by: the Russian Science Foundation (RNF), grant ¹14-31-00014 «Creating a breakthrough laboratory study of remote sensing." The results are set forth in the section "Methodology" and "proposed decision"; grants of the Russian Foundation for Basic Research ¹16-37-00043_mol_a, ¹15-07-01164-a. The results are set forth in the section "Experimental Research".


DOI: https://doi.org/10.18287/2412-6179-2016-40-1-526-534

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Full text: http://www.computeroptics.smr.ru/.../400412.html
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Received: 19.08.2016
Accepted:26.08.2016

Citation: A. Yu. Denisova, V. V. Myasnikov, “Atmospheric correction of hyperspectral images using small volume of the verified data”, Computer Optics, 40:4 (2016), 526–534

Citation in format AMSBIB
\Bibitem{DenMya16}
\by A.~Yu.~Denisova, V.~V.~Myasnikov
\paper Atmospheric correction of hyperspectral images using small volume of the verified data
\jour Computer Optics
\yr 2016
\vol 40
\issue 4
\pages 526--534
\mathnet{http://mi.mathnet.ru/co247}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-1-526-534}


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