Automatic DTM Generation from Three-Line-Scanner (TLS) Images

This paper presents a matching procedure for automatic DSM generation from the Three-Line-Scanner (TLS) raw images. It can provide dense, precise and reliable results. The proposed method combines matching procedures based on grid point matching and feature point matching. Modified Multiphoto Geometrically Constrained Matching (MPGC) and Geometrically Constrained Multipoint Matching (GCMM) are used to refine the relaxation matching results in order to achieving sub-pixel accuracy on the grid DSM. We match three TLS images and provide the pixel and object coordinates for grid points simultaneously. In order to compensate the disadvantages of terrain modeling by grid points, an additional feature-point matching procedure is performed. The feature points are extracted by using an interest operator such as Moravec’s. Then we activate the modified MPGC, using three TLS images simultaneously, and achieve potentially sub-pixel accuracy. The sensor model used for the geometric constraints derivation is based on the collinearity equations appended by some trajectory models. The algorithms proposed in this paper have been applied to different areas with varying textures and terrain types. The accuracy test is based on the comparison between well-distributed semi-automatically measured feature points and the automatic extracted DSMs, and on visual inspection of the results.