Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery

Chunping Qiu, Michael Schmitt, Xiao Xiang Zhu

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

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.

Original languageEnglish
Pages (from-to)218-231
Number of pages14
JournalISPRS Journal of Photogrammetry and Remote Sensing
Volume138
DOIs
StatePublished - Apr 2018

Keywords

  • Data fusion
  • Optical images
  • Remote sensing
  • Stereogrammetry
  • Synthetic Aperture Radar (SAR)

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