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Computer Optics, 2016, Volume 40, Issue 3, Pages 416–421
DOI: https://doi.org/10.18287/0134-2452-2016-40-3-416-421
(Mi co159)
 

This article is cited in 6 scientific papers (total in 6 papers)

SHORT MESSAGE

A parametric model for the autocorrelation function of space hyperspectral data

V. V. Sergeevab, R. R. Yuzkiva

a Samara National Research University, Samara, Russia
b Image Processing Systems Institute îf RAS,– Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia
Full-text PDF (441 kB) Citations (6)
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Abstract: A new parametric model for the autocorrelation function of space hyperspectral data has been proposed. A heuristic algorithm for estimating the model parameters has been developed. The proposed model has been demonstrated to provide a good approximation of the observed autocorrelation functions.
Keywords: autocorrelation function, space hyperspectral image, parametric model.
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."
Received: 20.05.2016
Accepted: 20.05.2016
Document Type: Article
Language: Russian
Citation: V. V. Sergeev, R. R. Yuzkiv, “A parametric model for the autocorrelation function of space hyperspectral data”, Computer Optics, 40:3 (2016), 416–421
Citation in format AMSBIB
\Bibitem{SerYuz16}
\by V.~V.~Sergeev, R.~R.~Yuzkiv
\paper A parametric model for the autocorrelation function of space hyperspectral data
\jour Computer Optics
\yr 2016
\vol 40
\issue 3
\pages 416--421
\mathnet{http://mi.mathnet.ru/co159}
\crossref{https://doi.org/10.18287/0134-2452-2016-40-3-416-421}
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  • https://www.mathnet.ru/eng/co/v40/i3/p416
  • This publication is cited in the following 6 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    Abstract page:215
    Full-text PDF :107
    References:26
     
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