An experiment in automated interpretation of remote sensing imagery

Автор: Lur’ye I.K.
Журнал: Mapping sciences and remote sensing
Том: 21
Номер: 3
Год издания: 1984
Первая страница: 255
Последняя страница: 261
DOI: 10.1080/07493878.1984.10641555
Аннотация: Algorithms, designed for digital image processing in standard mainframe computers and representing sequential stages in a land-use classification procedure, are used to produce maps of agricultural crop types from multispectral satellite imagery. Pixel reflectance values are first grouped according to an unsupervised “rapid classification algorithm,” or data compression procedure. Mean reflectance values of the resulting classes then go into a supervised “sequential clustering algorithm” where classes are refined according to training value and other parameter inputs. The objective is to increase the accessibility of automated image interpretation while balancing classification accuracy and processing time. Translated from: Vestnik Moskovskogo Universiteta, geografiya, 1984, No. 4, pp. 63-69.
Добавил в систему: Самсонов Тимофей Евгеньевич

	ИСТИНА	Войти в систему Регистрация
	ИПМех РАН
	Главная Поиск Статистика О проекте Помощь

ИСТИНА