Инд. авторы:	Borzov S.M., Potaturkin A.O., Potaturkin O.I., Fedotov A.M.
Заглавие:	Analysis of the efficiency of classification of hyperspectral satellite images of natural and man-made areas
Библ. ссылка:	Borzov S.M., Potaturkin A.O., Potaturkin O.I., Fedotov A.M. Analysis of the efficiency of classification of hyperspectral satellite images of natural and man-made areas // Optoelectronics, Instrumentation and Data Processing. - 2016. - Vol.52. - Iss. 1. - P.1-10. - ISSN 8756-6990. - EISSN 1934-7944.
Внешние системы:	DOI: 10.3103/S8756699016010015; РИНЦ: 27154333; SCOPUS: 2-s2.0-84969802383; WoS: 000381640200001;
Реферат:	eng: The efficiency of a number of the classical methods of supervised classification of hyperspectral data is estimated by an example of discriminating the types of the underlying surface in natural and man-made areas. The minimum distance, support vector machine, Mahalanobis, and maximum likelihood methods are considered. Particular attention is paid to studying the dependence of the data classification accuracy on the number of spectral features and the way of choosing them in the above-mentioned methods. Experimental results obtained by processing real hyperspectral images of landscapes of various types are reported. © 2016, Allerton Press, Inc.
Ключевые слова:	classification of surface types; Image classification; Underlying surface; Supervised classification; Reflection spectra; Maximum likelihood methods; Hyperspectral satellite; Hyperspectral Data; Hyper-spectral images; Data classification; Spectroscopy; Remote sensing; Maximum likelihood; Efficiency; Classification (of information); remote sensing; reflection spectrum; hyperspectral images;
Издано:	2016
Физ. характеристика:	с.1-10
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