DocumentCode :
1949266
Title :
A Classification Method of Multispectral Images Which Is Based on Fuzzy SVM
Author :
Huai-bin Wang ; Jing-hua Ma
Author_Institution :
Dept. of Comput., Tianjin Univ. of Technol., Tianjin
Volume :
1
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
815
Lastpage :
818
Abstract :
Support vector machine (SVM) is more popular in recent years in the field of pattern recognition algorithms. SVM algorithm has good validity of the calculation, statistical robustness and stability. SVM has gradually become an important tool in the field of remote sensing image classification. Because of the similarity between the different classes in the multispectral images, the result of the classification which is gotten by using the SVM directly is usually not satisfying. In this paper, we proposed a method based on fuzzy SVM (FSVM) to classify the multispectral images. The result of the experiment shows that the accuracy of this method is higher compared with the method which used the SVM directly.
Keywords :
fuzzy set theory; geophysical signal processing; image classification; remote sensing; spectral analysis; support vector machines; fuzzy SVM algorithm; multispectral image classification method; pattern recognition algorithm; remote sensing image classification; statistical robustness; support vector machine; Computer science; Image classification; Multispectral imaging; Pattern recognition; Remote sensing; Robust stability; Software algorithms; Software engineering; Support vector machine classification; Support vector machines; SVM; classification; fuzzy; multispectral images;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.784
Filename :
4721874
Link To Document :
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