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Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery.
Qiu, Chunping; Schmitt, Michael; Zhu, Xiao Xiang.
Afiliación
  • Qiu C; Signal Processing in Earth Observation, Technical University of Munich (TUM), Munich, Germany.
  • Schmitt M; Signal Processing in Earth Observation, Technical University of Munich (TUM), Munich, Germany.
  • Zhu XX; Signal Processing in Earth Observation, Technical University of Munich (TUM), Munich, Germany.
ISPRS J Photogramm Remote Sens ; 138: 218-231, 2018 Apr.
Article en En | MEDLINE | ID: mdl-29615830
ABSTRACT
In this paper we discuss the potential and challenges regarding SAR-optical stereogrammetry for urban areas, using very-high-resolution (VHR) remote sensing imagery. Since we do this mainly from a geometrical point of view, we first analyze the height reconstruction accuracy to be expected for different stereogrammetric configurations. Then, we propose a strategy for simultaneous tie point matching and 3D reconstruction, which exploits an epipolar-like search window constraint. To drive the matching and ensure some robustness, we combine different established hand-crafted similarity measures. For the experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR imagery is generally feasible with 3D positioning accuracies in the meter-domain, although the matching of these strongly hetereogeneous multi-sensor data remains very challenging.
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