Local Registration and Deformation of a Road Cartographic Database on A SPOT Satellite Image

Guillaume Rellier (1) , Xavier Descombes (1) , Josiane Zerubia (1)

1 ARIANA - Inverse problems in earth monitoring

Herein, we propose a local registration method for cartographic road networks on SPOT satellite images based on Markov Random Fields (MRF) on graphs. Since the cartographic and image data are obtained from exogeneous sources, the noises degrading these data are of different nature. This phenomenon can create important differences between the data. In addition, cartographers sometimes introduce distortions, in the so-called generalization process, in the road map in order to emphasize some details of the road (like the bends of a mountain road). The proposed algorithm aims at correcting the error due to noise and generalization, hence increasing the accuracy of the road map. The proposed method consists in translating the cartographic data into a graph model, and then defining a MRF to fit the graph on the image.

Mots clés: REMOTE SENSING; REGISTRATION; MARKOV RANDOM FIELDS; ROAD NETWORKS; CARTOGRAPHY

Domaines: Autre [cs.OH]

Guillaume Rellier, Xavier Descombes, Josiane Zerubia. Local Registration and Deformation of a Road Cartographic Database on A SPOT Satellite Image. [Research Report] RR-3939, INRIA. 2000, pp.20. ⟨inria-00072711⟩