DocumentCode
326907
Title
Classification of remote-sensing images by using the Bayes rule for minimum cost
Author
Bruzzone, Lorenzo
Author_Institution
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Volume
4
fYear
1998
fDate
6-10 Jul 1998
Firstpage
1778
Abstract
An approach based on the Bayes rule for minimum cost for feature selection and classification of remote-sensing images is proposed. This approach allows one to achieve land-cover maps in which the total cost involved by errors, instead of the total classification error, is minimized. Experiments carried out on a multisource data set of the Island of Elba (Italy) point out the effectiveness of the proposed minimum cost approach
Keywords
Bayes methods; geophysical signal processing; geophysical techniques; image classification; minimisation; remote sensing; Bayes rule; Bayesian method; feature extraction; feature selection; geophysical measurement technique; image classification; land surface; land-cover map; minimisation; minimization; minimum cost; minimum cost approach; remote sensing; terrain mapping; Costs; Electronic mail; Fires; Gravity; Neural networks; Pixel; Production; Remote sensing; Risk management; Satellites;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location
Seattle, WA
Print_ISBN
0-7803-4403-0
Type
conf
DOI
10.1109/IGARSS.1998.703649
Filename
703649
Link To Document