OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 18, Iss. 1 — Jan. 1, 2001
  • pp: 55–64

Scene illuminant classification: brighter is better

Shoji Tominaga, Satoru Ebisui, and Brian A. Wandell  »View Author Affiliations

JOSA A, Vol. 18, Issue 1, pp. 55-64 (2001)

View Full Text Article

Enhanced HTML    Acrobat PDF (1142 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Knowledge of the scene illuminant spectral power distribution is useful for many imaging applications, such as color image reproduction and automatic algorithms for image database applications. In many applications accurate spectral characterization of the illuminant is impossible because the input device acquires only three spectral samples. In such applications it is sensible to set a more limited objective of classifying the illuminant as belonging to one of several likely types. We describe a data set of natural images with measured illuminants for testing illuminant classification algorithms. One simple type of algorithm is described and evaluated by using the new data set. The empirical measurements show that illuminant information is more reliable in bright regions than in dark regions. Theoretical predictions of the algorithm’s classification performance with respect to scene illuminant blackbody color temperature are tested and confirmed by using the natural-image data set.

© 2001 Optical Society of America

OCIS Codes
(330.1690) Vision, color, and visual optics : Color

Original Manuscript: January 3, 2000
Revised Manuscript: July 11, 2000
Manuscript Accepted: July 11, 2000
Published: January 1, 2001

Shoji Tominaga, Satoru Ebisui, and Brian A. Wandell, "Scene illuminant classification: brighter is better," J. Opt. Soc. Am. A 18, 55-64 (2001)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. The image data used in this paper will be available at http://www.osakac.ac.jp/labs/shoji/ .
  2. D. B. Judd, D. L. MacAdam, W. S. Stiles, “Spectral distribution of typical daylight as a function of correlated color temperature,” J. Opt. Soc. Am. 54, 1031–1040 (1964). [CrossRef]
  3. L. T. Maloney, B. A. Wandell, “Color constancy: a method for recovering surface spectral reflectance,” J. Opt. Soc. Am. A 3, 29–33 (1986). [CrossRef] [PubMed]
  4. S. Tominaga, B. A. Wandell, “The standard surface reflectance model and illuminant estimation,” J. Opt. Soc. Am. A 6, 576–584 (1989). [CrossRef]
  5. B. V. Funt, M. S. Drew, J. Ho, “Color constancy from mutual reflection,” Int. J. Comput. Vis. 6, 5–24 (1991). [CrossRef]
  6. M. D’Zmura, G. Iverson, “Color constancy: I. Basic theory of two-stage linear recovery of spectral descriptions for lights and surfaces,” J. Opt. Soc. Am. A 10, 2148–2165 (1993). [CrossRef]
  7. M. D’Zmura, G. Iverson, B. Singer, “Probabilistic color constancy,” in R. D. Luce et al., eds., Geometric Representations of Perceptual Phenomena (Erlbaum, Mahway, N.J., 1995), pp. 187–202.
  8. S. Tominaga, “Multichannel vision system for estimating surface and illumination functions,” J. Opt. Soc. Am. A 13, 2163–2173 (1996). [CrossRef]
  9. D. H. Brainard, W. T. Freeman, “Bayesian color constancy,” J. Opt. Soc. Am. A 14, 1393–1411 (1997). [CrossRef]
  10. G. D. Finlayson, P. M. Hubel, S. Hordley, “Color by correlation,” in Proceedings of the Fifth Color Imaging Conference (Society for Imaging Science and Technology, Springfield, Va., 1997), pp. 6–11.
  11. G. D. Finlayson, “Color in perspective,” IEEE Trans. Pattern Anal. Mach. Intell. 18, 1034–1038 (1996). [CrossRef]
  12. G. Wyszecki, W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae (Wiley, New York, 1982).
  13. M. J. Vrhel, R. Gershon, L. S. Iwan, “Measurement and analysis of object reflectance spectra,” Color Res. Appl. 19, 4–9 (1994).
  14. S. Tominaga, S. Ebisui, B. A. Wandell, “Color temperature estimation of scene illumination,” in Proceedings of the Seventh Color Imaging Conference (Society for Imaging Science and Technology, Springfield, Va., 1999), pp. 42–47.
  15. D. A. Forstyth, “A novel algorithm for color constancy,” Int. J. Comput. Vis. 5, 5–36 (1990). [CrossRef]
  16. Y. Yu, P. Debevec, J. Malik, T. Hawkins, “Inverse global illumination: recovering reflectance models of real scenes from photographs,” Special Interest Group on Computer Graphics and Interactive Techniques (SIGGRAPH) 99, 215–224 (1999).
  17. D. H. Brainard, “Color constancy in the nearly natural image. 2. Achromatic loci,” J. Opt. Soc. Am. A 15, 307–325 (1998). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited