Improving active learning methods using spatial information
Edoardo Pasolli, Farid Melgani, Devis Tuia, Fabio Pacifici, William J. Emery · 2011
Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning.