Lazy yet efficient land-cover map generation for HR optical images

High resolution optical remote sensing images allow to produce accurate land-cover maps. This is usually achieved using an ad-hoc mixture of image segmentation and supervised classification. The main drawback of this approach is that it does not scale for real world complete scenes. In this paper we present a framework which allows to implement this kind of image analysis without scale issues.

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