The topic of this thesis is the usage of hyperspectral images and digital surface models for urban object extraction. A method for rectilinear building polygon extraction is proposed, which accounts for edge probabilities from both datasets. The edge probabilities are detected in a linear scale space and combined by a Bayesian fusion. They are introduced as weights in the adjustment of building polygons. A new quality measure for the evaluation of the extracted building polygons, named PoLiS metric, is defined and compared to the community accepted measures.
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The topic of this thesis is the usage of hyperspectral images and digital surface models for urban object extraction. A method for rectilinear building polygon extraction is proposed, which accounts for edge probabilities from both datasets. The edge probabilities are detected in a linear scale space and combined by a Bayesian fusion. They are introduced as weights in the adjustment of building polygons. A new quality measure for the evaluation of the extracted building polygons, named PoLiS met...
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