%0 Conference Proceedings
%4 dpi.inpe.br/plutao/2012/11.28.16.49
%2 dpi.inpe.br/plutao/2012/11.28.16.49.04
%F lattes: 8201805132981288 1 NegriDutrSant:2012:SuVeMa
%T Support Vector Machine and Bathacharrya Kernel Function for Region Based Classification
%D 2012
%A Negri, Rogério Galante,
%A Dutra, Luciano Vieira,
%A Sant'Anna, Sidinei João Siqueira,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress rogerio@dpi.inpe.br
%@electronicmailaddress dutra@dpi.inpe.br
%@electronicmailaddress sidnei@dpi.inpe.br
%B IEEE International Geoscience and Remote Sensing Symposium, 32 (IGARSS).
%C Munich
%8 2012
%S Proceedings
%K Region Based Classification, Support Vector Machine, Stochastic Distance, Bhattacharyya Kernel Function.
%X 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.
%@language en
%3 negri_support.pdf