Abstract
We present a semiautomatic approach to generate high quality digital terrain models (DTM) from digital surface models (DSM). A DTM is a model of the earths surface, where all man made objects and the vegetation have been removed. In order to achieve this, we use a variational energy minimization approach. The proposed energy functional incorporates Huber regularization to yield piecewise smooth surfaces and an L1 norm in the data fidelity term. Additionally, a minimum constraint is used in order to prevent the ground level from pulling up, while buildings and vegetation are pulled down. Being convex, the proposed formulation allows us to compute the globally optimal solution. Clearly, a fully automatic approach does not yield the desired result in all situations. Therefore, we additionally allow the user to affect the algorithm using different user interaction tools. Furthermore, we provide a real-time 3D visualization of the output of the algorithm which additionally helps the user to assess the final DTM. We present results of the proposed approach using several real data sets.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Belliss, S., Mcneill, S., Barringer, J., Pairman, D., North, H.: Digital terrain modelling for exploration and mining. In: Proceedings on New Zealand Minerals & Mining Conference (2000)
Paparoditis, N., Boudet, L., Tournaire, O.: Automatic man-made object extraction and 3D scene reconstruction from geomatic-images. Is there still a long way to go? In: Urban Remote Sensing Joint Event (2007)
Champion, N., Matikainen, L., Rottensteiner, F., Liang, X., Hyyppä, J.: A test of 2D building change detection methods: Comparison, evaluation and perspectives. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 37 (2008)
Eckstein, W., Munkelt, O.: Extracting objects from digital terrain models. In: Remote Sensing and Reconstruction for Three-Dimensional Objects and Scenes, SPIE, pp. 43–51 (1995)
Weidner, U., Förstner, W.: Towards automatic building extraction from high-resolution digital elevation models. ISPRS Journal of Photogrammetry and Remote Sensing 50, 38–49 (1995)
Zhang, K., Ching Chen, S., Whitman, D., Ling Shyu, M., Yan, J., Zhang, C., Member, S.: A progressive morphological filter for removing nonground measurements from airborne lidar data. IEEE Transactions on Geoscience and Remote Sensing 41, 872–882 (2003)
Champion, N., Boldo, D.: A robust algorithm for estimating digital terrain models from digital surface models in dense urban areas. In: PCV Photogrammetric Computer Vision (2006)
Sohn, G., Dowman, I.: Terrain surface reconstruction by the use of tetrahedron model with the mdl criterion. In: Photogrammetric Computer Vision, A, p. 336 (2002)
Rottensteiner, F.: Automatic generation of high-quality building models from lidar data. Computer Graphics and Applications, IEEE 23, 42–50 (2003)
Baillard, C., Maître, H.: 3-D reconstruction of urban scenes from aerial stereo imagery: a focusing strategy. Comput. Vis. Image Underst. 76, 244–258 (1999)
Sithole, G., Vosselman, G.: Filtering of airborne laser scanner data based on segmented point clouds. In: Workshop on Laser Scanning (2005)
Baillard, C.: A hybrid method for deriving dtms from urban dems. In: ISPRS International Society for Photogrammetry and Remote Sensing, vol. B3b, p. 109 (2008)
Zebedin, L., Klaus, A., Gruber Geymayer, B., Karner, K.: Towards 3D map generation from digital aerial images. ISPRS Journal of Photogrammetry and Remote Sensing 60, 413–427 (2006)
Pock, T., Unger, M., Cremers, D., Bischof, H.: Fast and exact solution of total variation models on the GPU. In: CVPR Workshop on Visual Computer Vision on GPU’s, Anchorage, Alaska, USA (2008)
Huber, P.: Robust Statistics. Wiley, New York (1981)
Tikhonov, A.: On the stability of inverse problems. Dokl. Akad. Nauk SSSR 39, 195–198 (1943)
Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Phys. D 60, 259–268 (1992)
Keeling, S.L.: Total variation based convex filters for medical imaging. Appl. Math. Comput. 139, 101–119 (2003)
Hintermüller, M., Stadler, G.: An infeasible primal-dual algorithm for total bounded variation–based inf-convolution-type image restoration. SIAM J. Sci. Comput. 28, 1–23 (2006)
Rockafellar, R.T.: Convex analysis. Princeton Landmarks in Mathematics. Princeton University Press, Princeton (1997); Reprint of the 1970 original, Princeton Paperbacks
Aujol, J.F., Gilboa, G., Chan, T., Osher, S.: Structure-texture image decomposition–modeling, algorithms, and parameter selection. Intl. J. of Computer Vision 67, 111–136 (2006)
Chan, T., Esedoglu, S.: Aspects of total variation regularized L 1 function approximation. SIAM Journal of Applied Mathematics 65, 1817–1837 (2004)
Chambolle, A.: Total variation minimization and a class of binary MRF models. In: Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 136–152 (2005)
Goldstein, T., Osher, S.: The split bregman method for L 1 regularized problems. UCLA CAM Report 08-29 (2008)
NVidia: NVidia CUDA Compute Unified Device Architecture programming guide 2.0. Technical report, NVIDA Corp., Santa Clara, CA, USA (2008)
Wernecke, J.: The Inventor Mentor. Addison-Wesley, Reading (1994)
Grabner, M.: On-the-fly greedy mesh simplification for 2\(\frac12\)D regular grid data acquisition systems. In: Proceedings Annual Conference of the Austrian Association for Pattern Recognition (AAPR), Graz, Austria, pp. 103–110 (2002)
Segal, M., Akeley, K.: The OpenGL graphics system: A specification. Technical report, The Khronos Group Inc. (2009), http://www.opengl.org
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: British Machine Vision Conference, vol. 1, pp. 384–393 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Unger, M., Pock, T., Grabner, M., Klaus, A., Bischof, H. (2009). A Variational Approach to Semiautomatic Generation of Digital Terrain Models. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10520-3_107
Download citation
DOI: https://doi.org/10.1007/978-3-642-10520-3_107
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10519-7
Online ISBN: 978-3-642-10520-3
eBook Packages: Computer ScienceComputer Science (R0)