Region Refinement and Parametric Reconstruction of Building Roofs by Integration of Image and Height Data

The refinement of the features extracted from image data is a key issue in automated building extraction since feature extraction algorithms often result in incomplete features. This paper describes a method for the integration of image and Lidar height data, which leads to the refinement of initial image regions and the reconstruction of the parametric forms of roof planes. Region refinement is based on fitting planar surfaces to the height points that project into each image region. The number and parameters of the planar surfaces are used to split and/or merge the incomplete regions. Every refined region corresponds to a single plane in object space whose average height over the average terrain height determines whether it is a roof plane. Experiments with the proposed method demonstrate the capability of the method in region refinement and roof plane reconstruction.