Color Stereo Matching Cost Applied to CFA Images

  • Hachem Halawana
  • Ludovic Macaire
  • François Cabestaing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5646)


Most color stereovision setups include single-sensor cameras which provide Color Filter Array (CFA) images. In those, a single color component is sampled at each pixel rather than the three required ones (R,G,B). We show that standard demosaicing techniques, used to interpolate missing components, are not well adapted when the resulting color pixels are matched for estimating image disparities. In order to avoid this problem while exploiting color information, we propose a new matching cost designed for dense stereovision based on pairs of CFA images.


Color stereovision CFA image Demosaicing 


  1. 1.
    Battiato, S., Guarnera, M., Messina, G., Tomaselli, V.: Recent patents on color demosaicing. Recent Patents on Computer Science 1(3), 194–207 (2008)CrossRefGoogle Scholar
  2. 2.
    Chambon, S., Crouzil, A.: Color stereo matching using correlation measures. In: SEE (ed.) Proceedings of the First International Conference on Complex Systems Intelligence and Modern Technological Applications, Cherbourg, France, September 2004, pp. 520–525 (2004)Google Scholar
  3. 3.
    Gouet, V., Montesinos, P., Pelé, D.: Stereo matching of color images using differential invariants. In: Proceedings of the 5th International Conference on Image Processing, ICIP 1998, Chicago, IL, USA, October 1998, vol. 2, pp. 152–156 (1998)Google Scholar
  4. 4.
    Gunturk, B.K., Glotzbach, J., Altunbasak, Y., Schafer, R.W., Mersereau, R.M.: Demosaicking: Color filter array interpolation. IEEE Signal Processing Magazine 22(1), 44–54 (2005)CrossRefGoogle Scholar
  5. 5.
    Hamilton, J.F., Adams, J.E.: Adaptive color plan interpolation in single sensor color electronic camera. US patent 5, 629, 734, to Eastman Kodak Co., Patent and Trademark Office, Washington, DC (May 1997)Google Scholar
  6. 6.
    Hirschmüller, H., Scharstein, D.: Evaluation of cost functions for stereo matching. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2007), Minneapolis, June 2007, pp. 1–8 (2007)Google Scholar
  7. 7.
    Lukac, R.: Single-Sensor Imaging: Methods and Applications for Digital Cameras. CRC Press, Boca Raton (2008)CrossRefGoogle Scholar
  8. 8.
    Pinhasov, E., Shimkin, N., Zeevi, Y.: Optimal usage of color for disparity estimation in stereo vision. In: 13th European Signal Processing Conference (EUSIPCO 2005), Antalya, Turkey (September 2005)Google Scholar
  9. 9.
    Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47, 7–42 (2002)CrossRefzbMATHGoogle Scholar
  10. 10.
    Yang, Y., Losson, O., Duvieubourg, L.: Quality evaluation of color demosaicing according to image resolution. In: Proceedings of the 3rd International Conference on Signal-Image Technology & Internet-based Systems (SITIS 2007), Shanghai Jiaotong University, China, December 2007, pp. 640–646 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Hachem Halawana
    • 1
  • Ludovic Macaire
    • 1
  • François Cabestaing
    • 1
  1. 1.LAGIS, USTL, Bât. P2, Cité ScientifiqueVilleneuve d’Ascq.France

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