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Computer Optics, 2016, Volume 40, Issue 3, Pages 380–387 (Mi co154)  

HUPERSPECTRAL DATA ANALYSIS

Estimation of parameters of a linear spectral mixture for hyperspectral images with atmospheric distortions

A. Y. Denisovaa, Y. N. Juravela, V. V. Myasnikovba

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 paper, we propose a novel method for estimating parameters of a linear spectral mixture for hyperspectral images. This method allows omitting a preliminary atmospheric correction of the input image. In order to derive a solution of the mixture problem different models of radiation transmission in atmosphere are considered. An evaluation of the effects of noise, the number of input pixels, and the number of signatures on the accuracy of the linear mixture coefficient restoration and the input pixel representation error is made.

Keywords: hyperspectral images, linear spectral mixture analysis, atmospheric correction.

Funding Agency Grant Number
Russian Science Foundation 14-31-00014
Work done at the expense of the grant of the Russian Scientific Fund (project ¹ 14-31-00014) «Creating a laboratory breakthrough technology of remote sensing of the Earth."


DOI: https://doi.org/10.18287/2412-6179-2016-40-3-380-387

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Full text: http://www.computeroptics.smr.ru/.../400310.html
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Received: 28.04.2016
Accepted:13.05.2016

Citation: A. Y. Denisova, Y. N. Juravel, V. V. Myasnikov, “Estimation of parameters of a linear spectral mixture for hyperspectral images with atmospheric distortions”, Computer Optics, 40:3 (2016), 380–387

Citation in format AMSBIB
\Bibitem{DenZhuMya16}
\by A.~Y.~Denisova, Y.~N.~Juravel, V.~V.~Myasnikov
\paper Estimation of parameters of a linear spectral mixture for hyperspectral images with atmospheric distortions
\jour Computer Optics
\yr 2016
\vol 40
\issue 3
\pages 380--387
\mathnet{http://mi.mathnet.ru/co154}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-3-380-387}


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