Building Extraction from Digital Elevation Model

Description

We aim to extract buildings from Digital Elevation Models. To achieve this goal, we define a point process whose points represent buildings. We then define a density for this point process which is split into two parts. When written as an energy this density consists of two fields : the first one is an "internal field" that allows us to model the prior knowledge we have on patterns of buildings in urban areas. For instance, we avoid overlapping buildings. the second one is an "external field" that makes the point process fit the data, ie. the Digital Elevation Model. Once we have defined this artificial likehood, we use a Metropolis Hastings Green sampler, which is an extension of Geyer and Møller algorithm to sample point processes. This gives an estimate of the observed urban area.We present results on real data provided by the French Mapping Institute (IGN).

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