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Spatio-Spectral Remote Sensing Image Classification With Graph Kernels

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3 Author(s)
Camps-Valls, G. ; Image Process. Lab., Univ. de Valencia, València, Spain ; Shervashidze, N. ; Borgwardt, K.M.

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.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:7 ,  Issue: 4 )