Spatial smoothing over the original hyperspectral data based on wavelet and partial differential equations (PDEs) are incorporated in the classifiers using composite kernel with kNN graphs. The kernels combine spectral-spatial relationships using the smoothed and original images. Experiments with real hyperspectral scenarios are presented. Comparison with recent graph based methods show that the proposed scheme improves existing methods.
['Santiago Velasco-Forero', 'Vidya Manian']
Improving Hyperspectral Image Classification based on Graphs using Spatial Preprocessing