Automatic estimation of fine terrain models from multiple high-resolution satellite images

In this paper, we present an automatic method for deriving Digital Terrain Models (DTM) from Digital Surface Models (DSM). The DTM generation is formalized here as the minimization of a given energy, defined by a data term and a regularization term. The main contribution of this paper lies in the specific module, introduced in the data term in order to filter outliers (non ground points present in the original DSM) so that the final terrain surface best fits true ground points (inliers). The method is here introduced and tested on a vegetated and hilly area. A comparison to ground truth is also performed and shows the geometric accuracy and the robustness of the approach.