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The problem of supervised classification of multiresolution images, which are composed of a higher resolution panchromatic channel and of several coarser resolution multispectral channels, is addressed in this paper by proposing a novel contextual method based on Markov random fields. The method iteratively exploits a linear mixture model for the relationships between data at different resolutions...
Land cover / land use classification of remotely sensed images is inherently geographical. The use of spatial information, accounting for neighborhood relationship and spatial smoothness of geographical objects, made its proofs in countless occasions and, especially when considering very high resolution images, methods ignoring spatial context do not perform well. In this paper, we propose a hybrid...
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