—This paper proposes a new mapping schema, named mapping, for filtering nonground objects from LiDAR data, and the generation of a digital terrain model. By extending the CSL model, mapping extracts the most contrasted connected-com-ponents from top-hat scale-space and attributes them for an adap-tive multicriterion filter definition. Areas of the most contrasted connected-components and the standard deviations of contained points' levels are considered for this purpose. Computational effi-ciency is achieved by arranging the input LiDAR data into a grid, represented by a Max-Tree. Since a constant number of passes over the grid is required, the time complexity of the proposed method is linear according to the number of grid-cells. As confirmed by the experiments, the average CPU execution time decreases by nearly 98%, while the average accuracy improves by up to 10% in com-parison with the related method.
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