Airborne oblique stereo image dense matching by integrating SIFT and SGM algorithm

Yaogan Xuebao/Journal of Remote Sensing

Volumn 19, Issue 3, 2015, Pages 431-442

  Wu, Jun ^a   Yao, Zexin ^a   Cheng, Menmen ^a  

^a GUILIN UNIVERSITY OF ELECTRONIC TECHNOLOGY   (China)

Author keywords

Dense matching; Oblique photogrammetry; SGM; SIFT

Indexed keywords

EID: 84935071532     PISSN: 10074619     EISSN: None     Source Type: Journal    
DOI: 10.11834/jrs.20154132     Document Type: Article

References (25)

1. Bookstein F L. 1989. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(6): 567-585 [DOI:10.1109/34.24792]
2. Boykov Y, Veksler O and Zabin R. 2001. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11): 1222-1239 [DOI:10.1109/34.969114]
3. Gerke M and Kerle N. 2011. Automatic structural seismic damage assessment with airborne oblique pictometry imagery. Photogrammetric Engineering and Remote Sensing, 77(9): 885-898 [DOI:10.14358/PERS.77.9.885]
4. Gehrke S, Morin K, Downey M, Boehrer N and Fuchs T. 2010. Semi-global matching: an alternative to LIDAR for DSM generation? Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Calgury, canada: 38(1)
5. Hua S G and Zeng L Y. 2007. Dense matching algorithm based on corner detection. Computer Engineering and Design, 28(5): 1092-1095 [DOI:10.3969/j.issn.1000-7024.2007.05.031]
6. Hirschmüller H. 2008. Stereo processing by semiglobal matching and mutual information. IEEE Transaction on Pattern Analysis and Machine Intelligence, 30(2): 328-341 [DOI:10.1109/TPAMI.2007.1166]
7. Kannala J and Brandt S S. 2007. Quasi-dense wide baseline matching using match propagation// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis: IEEE: 1-8 [DOI:10.1109/CVPR.2007.383247]
8. Lhuillier M and Quan L. 2000. Robust dense matching using local and global geometric constraints// Proceedings of the 15th International Conference on Pattern Recognition. Barcelona: IEEE: 968-972 [DOI:10.1109/ICPR.2000.905620]
9. Lhuillier M and Quan L. 2005. A quasi-dense approach to surface reconstruction from uncalibrated images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(3): 418-433 [DOI:10.1109/TPAMI.2005.44]
10. Ma S D and Zhang Z Y. 2003. Computer Vision: the Calculation Theory and Algorithm. Beijing: Science Press
11. Mikolajczyk K and Schmid C. 2004. Scale & affine invariant interest point detectors. International Journal of Computer Vision, 60(1): 63-86 [DOI:10.1023/B:VISI.0000027790.02288.f2]
12. Nils K and Schroth O R. 2003. Oblique aerial photography a status review. PE & RS, Stuttgart/Neubrandenburg, 69(1): 53-57
13. Nyaruhuma A P, Gerke M, Vosselman G and Mtalo G E. 2012. Verification of 2D building outlines using oblique airborne images. ISPRS Journal of Photogrammetry and Remote Sensing, 71: 62-75 [DOI:10.1016/j.isprsjprs.2012.04.007]
14. Petrie G. 2009. Systematic oblique aerial photography using multiple digital cameras. Photogrammetric Engineering & Remote Sensing, 75(2): 102-107
15. Scharstein D and Szeliski R. 2002. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1/3): 7-42 [DOI:10.1023/A:1014573219977]
16. Sun J, Li Y, Kang S B and Shum H Y. 2005. Symmetric stereo matching for occlusion handling// Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Beijing: IEEE: 399-406 [DOI:10.1109/CVPR.2005.337]
17. Sun J, Shun H Y and Zheng N N. 2003. Stereo matching using belief propagation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(7): 787-800 [DOI:10.1109/TPAMI.2003.1206509]
18. Szeliski R, Zabih R, Scharstein D, Veksler O, Kolmogorov V, Agarwala A, Tappen M and Rother C. 2006. A comparative study of energy minimization methods for markov random fields// Proceedings of the 9th European Conference on Computer Vision. Berlin: Springer-Verlag Press: 16-29 [DOI:10.1007/11744047_2]
19. Tang L, Wu C K and Chen Z Z. 2002. Image dense matching based on region growth with adaptive window. Pattern Recognition Letters, 23(10): 1169-1178 [DOI:10.1016/S0167-8655(02)00063-6]
20. Wang Y, Schultz S and Giuffrida F. 2008. Pictometry's proprietary airborne digital imaging system and its application in 3D city modelling. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 37: 1065-1069
21. Wen C H and Lu H. 2012. A Nobel Hessian-gabor based local interest point detection. Computer Applications and Software, 29(1): 15-18, 22 [DOI:10.3969/j.issn.1000-386X.2012.01.004]
22. Xu W Y, Huang X S, Liu Y H and Zhang W. 2011. A local characteristic scale selection method based on Gabor wavelets. Journal of Image and Graphics, 16(1): 72-78
23. Xu Z H, Zhang F, Sun F M and Hu Z Y. 2009. Quasi-dense matching by neighborhood transfer for fish-eye image. Acta Automatica Sinica, 35(9): 1159-1167 [DOI:10.3724/SP.J.1004.2009.01159]
24. Zhang Z X and Zhang J Q. 2002. Digital Photogrammetry. Wuhan: Wuhan University Press
25. Zhu Q, Wu B and Zhao J. 2007. Propagation strategies for stereo image matching based on the dynamic triangle constraint. ISPRS Journal of Photogrammetry and Remote Sensing, 62(4): 295-308 [DOI:10.1016/j.isprsjprs.2007.05.010]