A framework for SAR-optical stereogrammetry over urban areas

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 146, Issue , 2018, Pages 389-408

  Bagheri, Hossein ^a   Schmitt, Michael ^a   d'Angelo, Pablo ^b   Zhu, Xiao Xiang ^a,b  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

3D reconstruction; Dense image matching; Epipolarity constraint; Multi sensor block adjustment; SAR optical stereogrammetry

Indexed keywords

GEOMETRICAL OPTICS; IMAGE ENHANCEMENT; IMAGE MATCHING; IMAGE RECONSTRUCTION; INFORMATION USE; REMOTE SENSING; SENSOR DATA FUSION; SPACE-BASED RADAR; SPECTROSCOPY; SYNTHETIC APERTURE RADAR;

3D RECONSTRUCTION; BLOCK ADJUSTMENT; EARTH OBSERVATION DATA; EPIPOLARITY; RATIONAL POLYNOMIAL COEFFICIENTS; REMOTE SENSING SATELLITES; SAR-OPTICAL STEREOGRAMMETRY; VERY HIGH RESOLUTION;

RADAR IMAGING;

ACCURACY ASSESSMENT; IMAGE ANALYSIS; OPTICAL METHOD; PHOTOGRAMMETRY; RECONSTRUCTION; REMOTE SENSING; SATELLITE IMAGERY; SPECTRAL ANALYSIS; SYNTHETIC APERTURE RADAR; URBAN AREA;

EID: 85055474935     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2018.10.003     Document Type: Article

References (49)

1. Bagheri, H., Schmitt, M., d'Angelo, P., Zhu, X.X., Exploring the applicability of semi-global matching for SAR-optical stereogrammetry of urban scenes. ISPRS Int. Arch. Photogram. Remote Sens. Spatial Inform. Sci. 42:2 (2018), 43–48.
2. Bloom, A.L., Fielding, E.J., Fu, X.-Y., A demonstration of stereophotogrammetry with combined SIR-B and Landsat TM images. Int. J. Remote Sens. 9 (1988), 1023–1038.
3. Brown, M.Z., Burschka, D., Hager, G.D., Advances in computational stereo. IEEE Trans. Pattern Anal. Mach. Intell. 25 (2003), 993–1008.
4. Cho, W., Schenk, T., Madani, M., Resampling digital imagery to epipolar geometry. Int. Arch. Photogram. Remote Sens., 29, 1993, 404.
5. Curlander, J.C., Location of spaceborne SAR imagery. IEEE Trans. Geosci. Remote Sens. 22 (1982), 106–112.
6. Curlander, J.C., McDonough, R.N., Synthetic Aperture Radar, vol. 396, 1991, John Wiley & Sons, New York, NY, USA.
7. d'Angelo, P., Reinartz, P., DSM based orientation of large stereo satellite image blocks. ISPRS Int. Arch. Photogram. Remote Sens. Spatial Inform. Sci. 39:B1 (2012), 209–214.
8. DigitalGlobe, 2018. Accuracy of WorldView products. < https://dg-cms-uploads-production.s3.amazonaws.com/uploads/document/file/38/DG_ACCURACY_WP_V3.pdf> (accessed 03.18).
9. Egnal, G., Wildes, R.P., Detecting binocular half-occlusions: empirical comparisons of five approaches. IEEE Trans. Pattern Anal. Mach. Intell. 24 (2002), 1127–1133.
10. Eineder, M., Minet, C., Steigenberger, P., Cong, X., Fritz, T., Imaging geodesy–toward centimeter-level ranging accuracy with TerraSAR-X. IEEE Trans. Geosci. Remote Sens. 49 (2011), 661–671.
11. Fraser, C.S., Hanley, H.B., Bias-compensated RPCs for sensor orientation of high-resolution satellite imagery. Photogram. Eng. Remote Sens. 71 (2005), 909–915.
12. Fraser, C., Dial, G., Grodecki, J., Sensor orientation via RPCs. ISPRS J. Photogram. Remote Sens. 60 (2006), 182–194.
13. Grodecki, J., Dial, G., Block adjustment of high-resolution satellite images described by rational polynomials. Photogram. Eng. Remote Sens. 69 (2003), 59–68.
14. Grodecki, J., Dial, G., Lutes, J., Mathematical model for 3D feature extraction from multiple satellite images described by RPCs. ASPRS Annual Conference Proceedings, Denver, Colorado, 2004.
15. Gupta, R., Hartley, R.I., Linear pushbroom cameras. IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997), 963–975.
16. Gutjahr, K., Perko, R., Raggam, J., Schardt, M., The epipolarity constraint in stereo-radargrammetric DEM generation. IEEE Trans. Geosci. Remote Sens. 52 (2014), 5014–5022.
17. Hartley, R.I., Zisserman, A., Multiple View Geometry in Computer Vision. second ed., 2004, Cambridge University Press ISBN: 0521540518.
18. Hassaballah, M., Abdelmgeid, A.A., Alshazly, H.A., Image features detection, description and matching. Awad, A.I., Hassaballah, M., (eds.) Image Feature Detectors and Descriptors: Foundations and Applications, 2016, Springer International Publishing, 11–45.
19. Hirschmüller, H., Stereo processing by semiglobal matching and mutual information. IEEE Trans. Pattern Anal. Mach. Intell. 30 (2008), 328–341.
20. Hughes, L.H., Auer, S., Schmitt, M., Investigation of joint visibility between SAR and optical images of urban environments. ISPRS Ann. Photogram. Remote Sens. Spatial Inform. Sci. 4 (2018), 129–136.
21. Kim, T., A study on the epipolarity of linear pushbroom images. Photogram. Eng. Remote Sens. 66 (2000), 961–966.
22. Kratky, V., Rigorous photogrammetric processing of SPOT images at CCM Canada. ISPRS J. Photogram. Remote Sens. 44 (1989), 53–71.
23. Li, D., Zhang, Y., A rigorous SAR epipolar geometry modeling and application to 3D target reconstruction. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 6 (2013), 2316–2323.
24. Li, R., Zhou, F., Niu, X., Di, K., Integration of Ikonos and QuickBird imagery for geopositioning accuracy analysis. Photogram. Eng. Remote Sens., 73, 2007, 1067.
25. Merkle, N., Luo, W., Auer, S., Müller, R., Urtasun, R., Exploiting deep matching and SAR data for the geo-localization accuracy improvement of optical satellite images. Remote Sens., 9, 2017, 586.
26. Mitra, N.J., Nguyen, A., Guibas, L., Estimating surface normals in noisy point cloud data. Int. J. Comput. Geom. Appl. 14 (2004), 261–276.
27. Morgan, M., Kim, K., Jeong, S., Habib, A., Epipolar geometry of linear array scanners moving with constant velocity and constant attitude. ISPRS Int. Arch. Photogram. Remote Sens. Spatial Inform. Sci. 35 (2004), 508–513.
28. Morgan, M.F., El-Sheimy, N., Saalfeld, A., Epipolar resampling of linear array scanner scenes. (PhD dissertation), 2004, University of Calgary, Department of Geomatics Engineering.
29. Muja, M., Lowe, D.G., Fast approximate nearest neighbors with automatic algorithm configuration. VISAPP International Conference on Computer Vision Theory and Applications, 2009, 331–340.
30. Oh, J., Lee, W.H., Toth, C.K., Grejner-Brzezinska, D.A., Lee, C., A piecewise approach to epipolar resampling of pushbroom satellite images based on RPC. Photogram. Eng. Remote Sens. 76 (2010), 1353–1363.
31. Orun, A.B., A modified bundle adjustment software for SPOT imagery and photography: tradeoff. Photogram. Eng. Remote Sens. 60 (1994), 1431–1437.
32. Perko, R., Raggam, H., Gutjahr, K., Schardt, M., Using worldwide available TerraSAR-X data to calibrate the geo-location accuracy of optical sensors. 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011, 2551–2554.
33. Qiu, C., Schmitt, M., Zhu, X.X., Towards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery. ISPRS J. Photogram. Remote Sens. 138 (2018), 218–231.
34. Raggam, J., Almer, A., Strobl, D., A combination of SAR and optical line scanner imagery for stereoscopic extraction of 3D data. ISPRS J. Photogram. Remote Sens. 49 (1994), 11–21.
35. Scharstein, D., Szeliski, R., Zabih, R., A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Proceedings IEEE Workshop on Stereo and Multi-Baseline Vision (SMBV 2001), 2001, 131–140.
36. Schmitt, M., Zhu, X.X., Data fusion and remote sensing: an ever-growing relationship. IEEE Geosci. Remote Sens. Mag. 4 (2016), 6–23.
37. Schnabel, R., Klein, R., Octree-based point-cloud compression. Proceedings of the 3rd Eurographics/IEEE VGTC Conference on Point-Based Graphics, SPBG’06, 2006, Eurographics Association, Aire-la-Ville, Switzerland, 111–121.
38. Suri, S., Reinartz, P., Mutual-information-based registration of TerraSAR-X and Ikonos imagery in urban areas. IEEE Trans. Geosci. Remote Sens. 48 (2010), 939–949.
39. Tao, C., Hu, Y., Use of the rational function model for image rectification. Can. J. Remote Sens. 27 (2001), 593–602.
40. Tao, C.V., Hu, Y., A comprehensive study of the rational function model for photogrammetric processing. Photogram. Eng. Remote Sens. 67 (2001), 1347–1358.
41. Tao, C.V., Hu, Y., 3D reconstruction methods based on the rational function model. Photogram. Eng. Remote Sens. 68 (2002), 705–714.
42. Tao, C.V., Hu, Y., Jiang, W., Photogrammetric exploitation of Ikonos imagery for mapping applications. Int. J. Remote Sens. 25 (2004), 2833–2853.
43. Tikhonov, A., Arsenin, V.Y., Methods for Solving Ill-posed Problems. 1977, John Wiley and Sons, Inc.
44. Tong, X., Liu, S., Weng, Q., Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery. ISPRS J. Photogram. Remote Sens. 65 (2010), 218–226.
45. Toutin, T., Comparison of 3D physical and empirical models for generating DSMs from stereo HR images. Photogram. Eng. Remote Sens. 72 (2006), 597–604.
46. USGS, 2000. Shuttle Radar Topography Mission (SRTM) void filled. < https://lta.cr.usgs.gov/SRTMVF> (accessed 09.17).
47. Wegner, J.D., Ziehn, J.R., Soergel, U., Combining high-resolution optical and InSAR features for height estimation of buildings with flat roofs. IEEE Trans. Geosci. Remote Sens. 52 (2014), 5840–5854.
48. Zhang, L., He, X., Balz, T., Wei, X., Liao, M., Rational function modeling for spaceborne SAR datasets. ISPRS J. Photogram. Remote Sens. 66 (2011), 133–145.
49. Zhu, K., d'Angelo, P., Butenuth, M., A performance study on different stereo matching costs using airborne image sequences and satellite images. Stilla, U., Rottensteiner, F., Mayer, H., Jutzi, B., Butenuth, M., (eds.) Photogrammetric Image Analysis, 2011, Springer, Berlin, Heidelberg, 159–170.