GraphK [Graph Kernel for Support Vector Machines]
Authors	G. Camps-Valls, Nino Shervashidze and Karsten Borgwardt
Download	Full Matlab Package
Code for the paper (please cite this paper!)	Spatio-spectral Remote Sensing Image Classification with Graph Kernels G. Camps-Valls, Nino Shervashidze and Karsten Borgwardt IEEE Geoscience and Remote Sensing Letters, 7(4), 741-745, Oct. 2010
Abstract	This paper presents a graph kernel for spatio-spectral remote sensing image classification with support vector machines (SVM). 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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