Urban surface reconstruction in SAR tomography by graph-cuts.

Clément Rambour, Loïc Denis, Florence Tupin, Hélène Oriot, Yue Huang, Laurent Ferro-Famil

Abstract: Highlights • Scatterers in dense urban areas are most likely to be surface distributed. • The urban surface is piecewise smooth. • The urban surface is close to high intensity scatterers. • A ray from the sensor to the scene intersects the surface exactly once. • The surface corresponding to these priors can be estimated by graph-cut. Abstract SAR (Synthetic Aperture Radar) tomography reconstructs 3-D volumes from stacks of SAR images. High resolution satellites such as TerraSAR-X provide images that can be combined to produce 3-D models. In urban areas, sparsity priors are generally enforced during the tomographic inversion process in order to retrieve the location of scatterers seen within a given radar resolution cell. However, such priors often miss parts of the urban surfaces. Those missing parts are typically regions of flat areas such as ground or rooftops. This paper introduces a surface segmentation algorithm based on the computation of the optimal cut in a flow network. This segmentation process can be included within the 3-D reconstruction framework in order to improve the recovery of urban surfaces. Illustrations on a TerraSAR-X tomographic dataset demonstrate the potential of the approach to produce a 3-D model of urban surfaces such as ground, façades and rooftops. Previous article in issue Next article in issue MSC 41A05 41A10 65D05 65D17