DocumentCode
1772741
Title
A Dempster-Shafer evidence theory-based approach to object classification on multispectral/hyperspectral images
Author
Popov, M.A. ; Topolnitskiy, Maxim V.
Author_Institution
Sci. Centre for Aerosp. Res. of the Earth, Kiev, Ukraine
fYear
2014
fDate
9-11 July 2014
Firstpage
285
Lastpage
289
Abstract
The algorithm for object classification on multispectral/hyperspectral images based on the Dempster-Shafer evidence theory is represented. The algorithm allows detecting not only separate classes but also their composition, i.e. takes into account the “mixed” pixels inherent in the presence of medium spatial resolution images.
Keywords
hyperspectral imaging; image classification; image resolution; inference mechanisms; Dempster-Shafer evidence theory; hyperspectral image; medium spatial resolution images; multispectral image; object classification; Accuracy; Bayes methods; Classification algorithms; Covariance matrices; Hyperspectral imaging; Dempster-Shafer evidence theory; multispectral / hyperspectral images; object classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Technologies (DT), 2014 10th International Conference on
Conference_Location
Zilina
Type
conf
DOI
10.1109/DT.2014.6868729
Filename
6868729
Link To Document