Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
권호 표지
DOI QR코드

DOI QR Code

Topographic Information Extraction from Kompsat Satellite Stereo Data Using SGM

  • Jang, Yeong Jae (Dept. of Civil Engineering, Korea Maritime and Ocean University) ;
  • Lee, Jae Wang (Dept. of Civil Engineering, Korea Maritime and Ocean University) ;
  • Oh, Jae Hong (Dept. of Civil Engineering, Korea Maritime and Ocean University)
  • Received : 2019.09.18
  • Accepted : 2019.10.10
  • Published : 2019.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

DSM (Digital Surface Model) is a digital representation of ground surface topography or terrain that is widely used for hydrology, slope analysis, and urban planning. Aerial photogrammetry and LiDAR (Light Detection And Ranging) are main technology for urban DSM generation but high-resolution satellite imagery is the only ingredient for remote inaccessible areas. Traditional automated DSM generation method is based on correlation-based methods but recent study shows that a modern pixelwise image matching method, SGM (Semi-Global Matching) can be an alternative. Therefore this study investigated the application of SGM for Kompsat satellite data of KARI (Korea Aerospace Research Institute). Firstly, the sensor modeling was carried out for precise ground-to-image computation, followed by the epipolar image resampling for efficient stereo processing. Secondly, SGM was applied using different parameterizations. The generated DSM was evaluated with a reference DSM generated by the first pulse returns of the LIDAR reference dataset.

Keywords

References

  1. Aguilar, M., Saldana, M., and Aguilar, F. (2014), Generation and quality assessment of stereo-extracted DSM from GeoEye-1 and WorldView-2 imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 52, No. 2, pp. 1259-1271. https://doi.org/10.1109/TGRS.2013.2249521
  2. Alobeid, A., Jacobsen, K., and Heipke, C. (2010), Comparison of matching algorithms for DSM generation in urban areas from IKONOS imagery, Photogrammetric Engineering & Remote Sensing, Vol. 76, No. 9, pp. 1041-1050. https://doi.org/10.14358/PERS.76.9.1041
  3. Fraser, C.S. and Hanley, H.B. (2005), Bias-compensated RPCs for sensor orientation of high-resolution satellite imagery, Photogrammetric Engineering & Remote Sensing, ASPRS, Vol. 71, No. 8, pp. 909-915. https://doi.org/10.14358/PERS.71.8.909
  4. Ghuffar, S. (2016), Satellite stereo based digital surface model generation using semi global matching in object and image space, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. III-1, 12-19 July, Prague, Czech Republic, pp. 63-68.
  5. Gong, K. and Fritsch, D. (2018), Point cloud and digital surface model generation from high resolution multiple view stereo satellite imagery, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLII-2, 4-7 June, Riva del Garda, Italy, pp. 363-370.
  6. Hirschmuller, H. (2008), Stereo processing by semiglobal matching and mutual information, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 30, No. 2, pp. 328-341. https://doi.org/10.1109/TPAMI.2007.1166
  7. Maes, F. (1997), Multimodality image registration by maximization of mutual information, IEEE Transactions on Medical Imaging, Vol. 16, No.2, pp.187-198. https://doi.org/10.1109/42.563664
  8. Oh, J.H. and Lee, C.N. (2016). Extraction of digital elevation model using stereo matching with slope-adaptive patch transformation, KSCE Journal of Civil Engineering, Vol. 20, No. 7, pp. 2902-2909. https://doi.org/10.1007/s12205-016-1735-3
  9. Oh, J.H., Lee, W.H., Toth, C.K., Grejner-Brzezinska, D.A., and Lee, C.N. (2010), A piecewise approach to epipolar resampling of pushbroom satellite images based on RPC, Photogrammetric Engineering & Remote Sensing, Vol. 76, No. 12, pp. 1353-1363. https://doi.org/10.14358/PERS.76.12.1353
  10. OpenCV team (2019), Class StereoSGBM, OpenCV Doc, https://docs.opencv.org/java/2.4.9/org/opencv/calib3d/StereoSGBM.html (last date accessed: 18 September 2019).
  11. Poon, J., Fraser, C.S., and Chunsun, Z. (2007), Digital surface models from high resolution satellite imagery, Photogrammetric Engineering & Remote Sensing, Vol. 72, No. 11, pp. 1225-1231. https://doi.org/10.14358/PERS.72.11.1225

Cited by

  1. 분류영상과 에지영상을 이용한 입체 위성영상의 SGM 성능개선 vol.38, pp.6, 2019, https://doi.org/10.7848/ksgpc.2020.38.6.655