DocumentCode
2556174
Title
Non-parametric classification algorithm with an unknown class
Author
Gorte, B. ; Gorte-Kroupnova, N.
Author_Institution
Dept. of Geoinf., Int. Inst. for Aerosp. Survey & Earth Sci., Enschede, Netherlands
fYear
1995
fDate
21-23 Nov 1995
Firstpage
443
Lastpage
448
Abstract
In the classification of pixels of a multispectral image by methods of supervised classification, a problem can arise in case when an unknown class is present. In this paper, we suggest a method that gives good results in such a case. The method provides an estimation for a posteriori probability vectors (and consequently, classification), and, besides, estimates the prior probability of classes, including the unknown one, and thus, the areas occupied by every class
Keywords
image classification; probability; a posteriori probability vectors; classification algorithm; multispectral image; pixels; supervised classification; Classification algorithms; Electronic components; Geoscience; Nearest neighbor searches; Pixel; Printed circuits; Probability distribution; Remote sensing; Vegetation mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 1995. Proceedings., International Symposium on
Conference_Location
Coral Gables, FL
Print_ISBN
0-8186-7190-4
Type
conf
DOI
10.1109/ISCV.1995.477042
Filename
477042
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