Urban surface recovery through graph-cuts over SAR tomographic reconstruction

Clément Rambour (1, 2) , Loïc Denis (3, 4) , Florence Tupin (2) , Hélène Oriot (1)

1 DEMR, ONERA, Université Paris Saclay (COmUE) [Palaiseau]
2 LTCI - Laboratoire Traitement et Communication de l'Information
3 LHC - Laboratoire Hubert Curien
4 Mines Saint-Étienne MSE - École des Mines de Saint-Étienne

The understanding of tomograms can be a difficult task when the observed scene is complex. The Synthetic Aperture RADAR (SAR) ranging acquisition induces geometrical distortions depending on the local slope of the back-scattering surface. Over dense urban areas, this particular geometry produces tilted facades instead of straight buildings. Moreover the high dynamic in SAR images of urban areas may lead to 3-D representation with very bright voxels eclipsing other echoes. In this paper we present a graph-cut approach adapted to any tomographic reconstruction technique to segment the urban surface in a 3-D tomographic reconstruction. Results on real data from a stack of 40 TerraSAR-X images are presented.

Mots clés: SAR; tomography; graph-cuts; urban areas

Domaines: Traitement du signal et de l'image [eess.SP]

Clément Rambour, Loïc Denis, Florence Tupin, Hélène Oriot. Urban surface recovery through graph-cuts over SAR tomographic reconstruction. 2019 Joint Urban Remote Sensing Event (JURSE), May 2019, Vannes, France. ⟨10.1109/JURSE.2019.8809001⟩. ⟨hal-02924933⟩