Инд. авторы:	Borzov S.M., Potaturkin O.I.
Заглавие:	Efficiency of the Spectral-Spatial Classification of Hyperspectral Imaging Data
Библ. ссылка:	Borzov S.M., Potaturkin O.I. Efficiency of the Spectral-Spatial Classification of Hyperspectral Imaging Data // Optoelectronics, Instrumentation and Data Processing. - 2017. - Vol.53. - Iss. 1. - P.26-34. - ISSN 8756-6990. - EISSN 1934-7944.
Внешние системы:	DOI: 10.3103/S8756699017010058; SCOPUS: 2-s2.0-85018508518; WoS: 000400565600005;
Реферат:	eng: The efficiency of methods of the spectral-spatial classification of similarly looking types of vegetation on the basis of hyperspectral data of remote sensing of the Earth, which take into account local neighborhoods of analyzed image pixels, is experimentally studied. Algorithms that involve spatial pre-processing of the raw data and post-processing of pixel-based spectral classification maps are considered. Results obtained both for a large-size hyperspectral image and for its test fragment with different methods of training set construction are reported. The classification accuracy in all cases is estimated through comparisons of ground-truth data and classification maps formed by using the compared methods. The reasons for the differences in these estimates are discussed.
Ключевые слова:	IMAGES; hyperspectral images; spectral and spatial features; fragments; classification of underlying surface types; remote sensing;
Издано:	2017
Физ. характеристика:	с.26-34