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Computer Optics, 2017, Volume 41, Issue 3, Pages 431–440 (Mi co403)  

IMAGE PROCESSING, PATTERN RECOGNITION

Hybrid methods for automatic landscape change detection in noisy data environment

A. A. Afanasyev, A. V. Zamyatin

National Research Tomsk State University, Tomsk, Russia

Abstract: We consider most widely used practical methods for land cover change detection based on remote data sensing. Based on these methods, approaches to constructing hybrid methods are proposed. Results of the experimental study of the proposed methods in the presence of noise of various types and intensities are discussed. Based on the results of the experiments, hybrid methods that allow one to achieve a better quality in automatic change detection when compared to the known methods are determined.

Keywords: landscape cover, change detection, landscape dynamics, change detection hybrid methods, digital image processing, image analysis, remote sensing and sensors, detection.

Funding Agency Grant Number
Ministry of Education and Science of the Russian Federation 2.4218.2017/4.6
Russian Foundation for Basic Research 14-07-00127
The results were obtained within the work on state task of the Ministry of Education and Science of the Russian Federation, project No. 2.4218.2017 / 4.6, and with the support of the Russian Foundation for Basic Research (grant No. 14-07-00127a).


DOI: https://doi.org/10.18287/2412-6179-2017-41-3-431-440

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Full text: http://www.computeroptics.smr.ru/.../410317.html
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Received: 14.03.2017
Accepted:25.05.2017

Citation: A. A. Afanasyev, A. V. Zamyatin, “Hybrid methods for automatic landscape change detection in noisy data environment”, Computer Optics, 41:3 (2017), 431–440

Citation in format AMSBIB
\Bibitem{AfaZam17}
\by A.~A.~Afanasyev, A.~V.~Zamyatin
\paper Hybrid methods for automatic landscape change detection in noisy data environment
\jour Computer Optics
\yr 2017
\vol 41
\issue 3
\pages 431--440
\mathnet{http://mi.mathnet.ru/co403}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-3-431-440}


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