DocumentCode :
2232820
Title :
Support Vector Machine and Bhattacharrya kernel function for region based classification
Author :
Negri, Rogério Galante ; Dutra, Luciano Vieira ; Sant´Anna, Sidnei João Siqueira
Author_Institution :
Inst. Nac. de Pesquisas Espaciais - INPE, São José dos Campos, Brazil
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
5422
Lastpage :
5425
Abstract :
Region based methods are indicated to classify image with strong heterogeneity, where only the spectral information is not enough. Different approaches have been proposed to perform this kind of classification. This study presents a new approach for region based classification that consists in use the Support Vector Machine (SVM) method with Bhattacharyya kernel function. A high resolution IKONOS image was classified. The classification results shows that SVM method using the Bhattacharyya kernel is better than Minimum Distance Classifier and conventional SVM.
Keywords :
geophysical image processing; image classification; image resolution; stochastic processes; support vector machines; Bhattacharrya kernel function; IKONOS image; SVM method; image classification; minimum distance classifier; region based classification; region based methods; support vector machine method; Kernel; Remote sensing; Rivers; Soil; Stochastic processes; Support vector machines; Training; Bhattacharyya kernel function; Region based classification; Support Vector Machine; stochastic distances;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352380
Filename :
6352380
Link To Document :
بازگشت