Simultaneous Multispectral Imaging and Illuminant Estimation Using a Stereo Camera

  • Raju Shrestha
  • Jon Yngve Hardeberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)


We propose here a novel approach to acquire a multispectral image and at the same time estimate the illuminant with the use of a stereo camera. Two images of a scene: one normal RGB and one filtered image with an appropriate optical filter selected from among readily available filters placed in front of a lens of the stereo camera are acquired. The spectral reflectance and/or color at each pixel on the scene are estimated from the corresponding outputs in the two images. In the mean time, the illuminant used during the image capture is estimated using chromagenic illuminant estimation method. Experiments with the simulated data show that this is a promising technique for simultaneous multispectral imaging and the illuminant estimation. Today’s increasing commercial availability of digital stereo cameras makes the proposed solution a viable one for many applications.


Root Mean Square Hyperspectral Image Multispectral Image Angular Error Stereo Camera 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Barnard, K., Cardei, V.C., Funt, B.: A comparison of computational color constancy algorithms. i: Methodology and experiments with synthesized data. IEEE Transactions on Image Processing 11(9), 972–984 (2002)CrossRefGoogle Scholar
  2. 2.
    Buchsbaum, G.: A spatial processor model for object colour perception. Journal of the Franklin Institute 310(1), 1–26 (1980)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Connah, D.R., Hardeberg, J.Y.: Spectral recovery using polynomial models. In: Color Imaging X: Processing, Hardcopy, and Applications. SPIE Proceedings, vol. 5667, pp. 65–75 (2005)Google Scholar
  4. 4.
    Finlayson, G.D., Hordley, S.D., Morovic, P.: Chromagenic colour constancy. In: 10th Congress of the International Colour Association (AIC), Granada, Spain, pp. 8–13 (May 2005)Google Scholar
  5. 5.
    Finlayson, G.D., Hordley, S.D., Morovic, P.: Chromagenic filter design. In: 10th Congress of the International Colour Association (AIC), Granada, Spain, pp. 1079–1083 (May 2005)Google Scholar
  6. 6.
    Hardeberg, J.Y., Schmitt, F., Brettel, H.: Multispectral color image capture using a liquid crystal tunable filter. Optical Engineering 41(10), 2532–2548 (2002)CrossRefGoogle Scholar
  7. 7.
    Hordley, S.D., Finlayson, G.D.: Reevaluation of color constancy algorithm performance. J. Opt. Soc. Am. A 23(5), 1008–1020 (2006)CrossRefGoogle Scholar
  8. 8.
    Huang, H.H.: Acquisition of multispectral images using digital cameras. In: Asian Association on Remote Sensing, ACRS (2004)Google Scholar
  9. 9.
    Imai, F.H., Berns, R.S.: Spectral estimation using trichromatic digital cameras. In: International Symposium on Multispectral Imaging and Color Reproduction for Digital Archives, pp. 42–49 (1999)Google Scholar
  10. 10.
    Land, E.H.: The retinex theory of color vision. Scientific American 237(6), 108–128 (1977)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Maloney, L.T., Wandell, B.A.: Color constancy: a method for recovering surface spectral reflectance. J. Opt. Soc. Am. A 3(1), 29–33 (1986)CrossRefGoogle Scholar
  12. 12.
    Mansouri, A., Marzani, F.S., Gouton, P.: Neural networks in two cascade algorithms for spectral reflectance reconstruction. In: IEEE International Conference on Image Processing, pp. 2053–2056 (2005)Google Scholar
  13. 13.
    Nascimento, S.M.C., Ferreira, F.P., Foster, D.H.: Statistics of spatial cone-excitation ratios in natural scenes. J. Opt. Soc. Am. A 19(8), 1484–1490 (2002)CrossRefGoogle Scholar
  14. 14.
    Omega: Omega filters. Omega Optical, Inc., (last visited: February 2012)
  15. 15.
    Pellegri, P., Novati, G., Schettini, R.: Selection of training sets for the characterisation of multispectral imaging systems. In: PICS, pp. 461–466 (2003)Google Scholar
  16. 16.
    Shrestha, R., Hardeberg, J.Y., Mansouri, A.: One-shot multispectral color imaging with a stereo camera. In: Digital Photography VII, Electronic Imaging, Proceedings of SPIE/IS&T Electronic Imaging, vol. 7876, p. 787609. SPIE, San Francisco (2011)Google Scholar
  17. 17.
    Shrestha, R., Mansouri, A., Hardeberg, J.Y.: Multispectral imaging using a stereo camera: Concept, design and assessment. EURASIP Journal on Advances in Signal Processing 2011(1) (September 2011)Google Scholar
  18. 18.
    Takita, K., Aoki, T., Sasaki, Y., Higuchi, T., Kobayashi, K.: High-accuracy subpixel image registration based on phase-only correlation. IEICE Trans. Fundamentals E86-A(8), 1925–1934 (2003)Google Scholar
  19. 19.
    Yamaguchi, M., Haneishi, H., Ohyama, N.: Beyond Red–Green–Blue (RGB): Spectrum-based color imaging technology. Journal of Imaging Science and Technology 52(1), 10201 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Raju Shrestha
    • 1
  • Jon Yngve Hardeberg
    • 1
  1. 1.The Norwegian Color Research LaboratoryGjøvik University CollegeGjøvikNorway

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