期刊
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 7, 期 4, 页码 741-745出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2010.2046618
关键词
Graphs; kernel methods; spatio-spectral image classification; support vector machine (SVM)
类别
资金
- Spanish Ministry of Education and Science [TEC2009-13696, AYA2008-05965-C04-03, CONSOLIDER/CSD2007-00018]
This letter presents a graph kernel for spatio-spectral remote sensing image classification with support vector machines (SVMs). The method considers higher order relations in the neighborhood (beyond pairwise spatial relations) to iteratively compute a kernel matrix for SVM learning. The proposed kernel is easy to compute and constitutes a powerful alternative to existing approaches. The capabilities of the method are illustrated in several multi- and hyperspectral remote sensing images acquired over both urban and agricultural areas.
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