EVALUATION OF STEREO MATCHING COSTS ON CLOSE RANGE, AERIAL AND SATELLITE IMAGES

Ke Zhu, Pablo d’Angelo, Matthias Butenuth

2012

Abstract

In the last years, most dense stereo matching methods use evaluation on the Middlebury stereo vision benchmark datasets. Most recent stereo algorithms were designed to perform well on these close range stereo datasets with relatively small baselines and good radiometric behaviour. In this paper, different matching costs on the Semi-Global Matching algorithm are evaluated and compared using the common Middlebury datasets, aerial and satellite datasets with ground truth. The experimental results show that the performance of dense stereo methods for datasets with larger baselines and stronger radiometric changes relies on even more robust matching costs. In addition, a novel matching cost based on mutual information and Census is introduced showing the most robust performance on close range, aerial and satellite data.

References

  1. Birchfield, S. and Tomasi, C. (1998). A pixel dissimilarity measure that is insensitive to image sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(4):401-406.
  2. Brockers, R. (2009). Cooperative stereo matching with color-based adaptive local support. Computer Analysis of Images and Patterns.
  3. Chrastek, R. and Jan, J. (1997). Mutual information as a matching criterion for stereo pairs of images. Analysis of Biomedical Signals and Images, 14:101-103.
  4. Hirschmüller, H. (2008). Stereo processing by semi-global matching and mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2):328-341.
  5. Hirschmüller, H. and Scharstein, D. (2009). Evaluation of stereo matching costs on image with radiometric differences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(9):1582-1599.
  6. Kurz, F., Müller, R., Stephani, M., Reinartz, P., and Schroeder, M. (2007). Calibration of a wide-angle digital camera system for near real time scenarios. ISPRS Workshop High Resolution Earth Imaging for Geospatial Information.
  7. Neilso, D. and Yang, Y. (2008). Evaluation of constructable match cost measures for stereo correspondence using cluster ranking. IEEE Conference on Computer Vision and Pattern Recognition.
  8. Reinartz, P., d'Angelo, P., Krauß, T., Poli, D., Jacobsen, K., and Buyuksalih, G. (2010). Benchmarking and quality analysis of dem generated from high and very high resolution optical stereo satellite data. ISPRS Symposium Commission I.
  9. Scharstein, D. and Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1):7-42.
  10. Scharstein, D. and Szeliski, R. (2011). Middlebury stereo vision research page. http://vision.middlebury.edu/ stereo/.
  11. Viola, P. and Wells, W. M. (1997). Alignment by maximization of mutual information. International Journal of Computer Vision, 24(2):137-154.
  12. Zabih, R. and Woodfill, J. (1994). Non-parametric local transforms for computing visual correspondancen. In Proc. European Conference of Computer Vision.
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Paper Citation


in Harvard Style

Zhu K., d’Angelo P. and Butenuth M. (2012). EVALUATION OF STEREO MATCHING COSTS ON CLOSE RANGE, AERIAL AND SATELLITE IMAGES . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: PRARSHIA, (ICPRAM 2012) ISBN 978-989-8425-98-0, pages 379-385. DOI: 10.5220/0003764203790385


in Bibtex Style

@conference{prarshia12,
author={Ke Zhu and Pablo d’Angelo and Matthias Butenuth},
title={EVALUATION OF STEREO MATCHING COSTS ON CLOSE RANGE, AERIAL AND SATELLITE IMAGES},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: PRARSHIA, (ICPRAM 2012)},
year={2012},
pages={379-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003764203790385},
isbn={978-989-8425-98-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: PRARSHIA, (ICPRAM 2012)
TI - EVALUATION OF STEREO MATCHING COSTS ON CLOSE RANGE, AERIAL AND SATELLITE IMAGES
SN - 978-989-8425-98-0
AU - Zhu K.
AU - d’Angelo P.
AU - Butenuth M.
PY - 2012
SP - 379
EP - 385
DO - 10.5220/0003764203790385