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
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;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.703649
