Local Registration and Deformation of a Road Cartographic Database on A SPOT Satellite Image
- Others:
- Inverse problems in earth monitoring (ARIANA) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Signal, Images et Systèmes (Laboratoire I3S - SIS) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- INRIA
Description
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.
Additional details
- URL
- https://hal.inria.fr/inria-00072711
- URN
- urn:oai:HAL:inria-00072711v1
- Origin repository
- UNICA