Skip to main content
SpringerLink
Log in

Color Constancy

  • Living reference work entry
  • Latest version View entry history
  • First Online:
Encyclopedia of Color Science and Technology

  • 314 Accesses

Definition

Color constancy refers to the ability of the visual system to perceive stable object colors, despite spatial and temporal change, as well as spectral changes, in the illumination. It is a prime example of perceptual constancy [1]. In daily life, humans and animals often count on color constancy to identify, discriminate, and search objects, as well as to judge physical and functional properties of objects. In a related concept, in machine vision, white balancing algorithms in cameras and image acquisition systems are widely used [2, 3]. Color constancy has been an active research topic in the past 100 years. For a thorough understanding of this subject, please see the following recent reviews and papers [4,5,6,7,8,9,10,11,12,13,14,15].

Human Color Constancy

Figure 1shows photos of the same scene under two illumination conditions. The left photo was taken in the morning when the dominant light source is the daylight, while the right was taken in the evening when the...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Walsh, V., Kulikowski, J.: Perceptual Constancy: why Things Look as they Do. Cambridge University Press (1998)

    Google Scholar 

  2. Helmholtz, H.V.: LXIII. On integrals of the hydrodynamical equations, which express vortex-motion. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science. 33(226), 485–512 (1867)

    Google Scholar 

  3. Shepard, R.N.: Perceptual-cognitive universals as reflections of the world. Behav. Brain Sci. 24(4), 581–601 (2001)

    Google Scholar 

  4. Brainard, D.H., Maloney, L.T.: Perception of color and material properties in complex scenes. J. Vis. 4(9), i–i (2004)

    Google Scholar 

  5. Zaidi, Q., Clifford, C., Rhodes, G.: The Role of Adaptation in Colour Constancy. Oxford University, Oxford (2005)

    Google Scholar 

  6. Smithson, H.E.: Sensory, computational and cognitive components of human colour constancy. Philosophical Transactions of the Royal Society B: Biological Sciences. 360(1458), 1329–1346 (2005)

    Google Scholar 

  7. Hurlbert, A.: Colour constancy. Curr. Biol. 17(21), R906–R907 (2007)

    Google Scholar 

  8. Shevell, S.K., Kingdom, F.A.: Color in complex scenes. Annu. Rev. Psychol. 59, 143–166 (2008)

    Google Scholar 

  9. Maloney, L.T., Brainard, D.H.: Color and material perception: achievements and challenges. J. Vis. 10(9), 19–19 (2010)

    Google Scholar 

  10. Foster, D.H.: Color constancy. Vis. Res. 51(7), 674–700 (2011)

    Google Scholar 

  11. Stockman, A., Brainard, D.H.: Color vision mechanisms. OSA Handbook of Optics. 11–11 (2010)

    Google Scholar 

  12. Bianco, S., Schettini, R.: Computational color constancy. In: 3rd European Workshop on Visual Information Processing, pp. 1–7. IEEE (2011)

    Google Scholar 

  13. Olkkonen, M., Ekroll, V.: Color constancy and contextual effects on color appearance. In: Human Color Vision, pp. 159–188. Springer, Cham (2016)

    Google Scholar 

  14. Witzel, C., Gegenfurtner, K.R.: Color perception: objects, constancy, and categories. Ann. Rev. Vis. Sci. 475–499 (2018)

    Google Scholar 

  15. Hurlbert, A.: Challenges to color constancy in a contemporary light. Curr. Opin. Behav. Sci. 30, 186–193 (2019)

    Google Scholar 

  16. Kraft, J.M., Brainard, D.H.: Mechanisms of color constancy under nearly natural viewing. Proc. Natl. Acad. Sci. 96(1), 307–312 (1999)

    ADS  Google Scholar 

  17. Maloney LT. Physics-based approaches to modeling surface color perception. Color Vision: From Genes to Perception. 1999; p. 387–416

    Google Scholar 

  18. Witzel, C., van Alphen, C., Godau, C., O’Regan, J.K.: Uncertainty of sensory signal explains variation of color constancy. J. Vis. 16(15), 8–8 (2016)

    Google Scholar 

  19. Aston, S., Radonjić, A., Brainard, D.H., Hurlbert, A.C.: Illumination discrimination for chromatically biased illuminations: implications for color constancy. J. Vis. 19(3), 15–15 (2019)

    Google Scholar 

  20. Bäuml, K.H.: Simultaneous color constancy: how surface color perception varies with the illuminant. Vis. Res. 39(8), 1531–1550 (1999)

    Google Scholar 

  21. Radonjić, A., Cottaris, N.P., Brainard, D.H.: Color constancy supports cross-illumination color selection. J. Vis. 15(6), 13–13 (2015)

    Google Scholar 

  22. Radonjić, A., Brainard, D.H.: The nature of instructional effects in color constancy. J. Exp. Psychol. Hum. Percept. Perform. 42(6), 847 (2016)

    Google Scholar 

  23. Brainard, D.H.: Color constancy in the nearly natural image. 2. Achromatic loci. JOSA A. 15(2), 307–325 (1998)

    ADS  Google Scholar 

  24. Hansen, T., Walter, S., Gegenfurtner, K.R.: Effects of spatial and temporal context on color categories and color constancy. J. Vis. 7(4), 2–2 (2007)

    Google Scholar 

  25. Murray, I.J., Daugirdiene, A., Stanikunas, R., Vaitkevicius, H., Kulikowski, J.: Cone contrasts do not predict color constancy. Vis. Neurosci. 23(3–4), 543–547 (2006)

    Google Scholar 

  26. Rinner, O., Gegenfurtner, K.R.: Cone contributions to colour constancy. Perception. 31(6), 733–746 (2002)

    Google Scholar 

  27. Olkkonen, M., Allred, S.R.: Short-term memory affects color perception in context. PLoS One. 9(1), (2014)

    Google Scholar 

  28. Xiao, B., Hurst, B., MacIntyre, L., Brainard, D.H.: The color constancy of three-dimensional objects. J. Vis. 12(4), 6–6 (2012)

    Google Scholar 

  29. Hurlbert, A.C., Ling, Y.: If it’s a banana, it must be yellow: the role of memory colors in color constancy. J. Vis. 5(8), 787–787 (2005)

    Google Scholar 

  30. Olkkonen, M., Hansen, T., Gegenfurtner, K.R.: Color appearance of familiar objects: effects of object shape, texture, and illumination changes. J. Vis. 8(5), 13–13 (2008)

    Google Scholar 

  31. Olkkonen, M., Witzel, C., Hansen, T., Gegenfurtner, K.R.: Categorical color constancy for real surfaces. J. Vis. 10(9), 16–16 (2010)

    Google Scholar 

  32. Smet, K., Ryckaert, W.R., Pointer, M.R., Deconinck, G., Hanselaer, P.: Colour appearance rating of familiar real objects. Color Res. Appl. 36(3), 192–200 (2011)

    Google Scholar 

  33. Kanematsu, E., Brainard, D.H.: No measured effect of a familiar contextual object on color constancy. Color Res. Appl. 39(4), 347–359 (2014)

    Google Scholar 

  34. Werner, A.: Color constancy improves, when an object moves: high-level motion influences color perception. J. Vis. 7(14), 19–19 (2007)

    Google Scholar 

  35. Yang, J.N., Maloney, L.T.: Illuminant cues in surface color perception: tests of three candidate cues. Vis. Res. 41(20), 2581–2600 (2001)

    Google Scholar 

  36. Granzier, J.J., Vergne, R., Gegenfurtner, K.R.: The effects of surface gloss and roughness on color constancy for real 3-D objects. J. Vis. 14(2), 16–16 (2014)

    Google Scholar 

  37. Lee, R.J., Smithson, H.E.: Low levels of specularity support operational color constancy, particularly when surface and illumination geometry can be inferred. JOSA A. 33(3), A306–A318 (2016)

    ADS  Google Scholar 

  38. Bloj, M.G., Kersten, D., Hurlbert, A.C.: Perception of three-dimensional shape influences colour perception through mutual illumination. Nature. 402(6764), 877–879 (1999)

    ADS  Google Scholar 

  39. Hedrich, M., Bloj, M., Ruppertsberg, A.I.: Color constancy improves for real 3D objects. J. Vis. 9(4), 16–16 (2009)

    Google Scholar 

  40. Jin, E.W., Shevell, S.K.: Color memory and color constancy. JOSA A. 13(10), 1981–1991 (1996)

    ADS  Google Scholar 

  41. Ling, Y., Hurlbert, A.: Role of color memory in successive color constancy. JOSA A. 25(6), 1215–1226 (2008)

    ADS  Google Scholar 

  42. Witzel, C., Hansen, T.: Memory effects on color perception. In: Elliot, A.J., Franklin, A., Fairchild, M.D. (eds.) Handbook of Color Psychology, pp. 639–640. Cambridge University Press, Cambridge, UK (2015)

    Google Scholar 

  43. Granzier, J.J., Gegenfurtner, K.R.: Effects of memory colour on colour constancy for unknown coloured objects. i-Perception. 3(3), 190–215 (2012)

    Google Scholar 

  44. Álvaro, L., Linhares, J.M., Moreira, H., Lillo, J., Nascimento, S.M.: Robust colour constancy in red-green dichromats. PLoS One. 12(6), e0180310 (2017)

    Google Scholar 

  45. Winkler, A.D., Spillmann, L., Werner, J.S., Webster, M.A.: Asymmetries in blue–yellow color perception and in the color of ‘the dress’. Curr. Biol. 25(13), R547–R548 (2015)

    Google Scholar 

  46. Radonjic, A., Pearce, B., Aston, S., Krieger, A., Dubin, H., Cottaris, N.P., et al.: Illumination discrimination in real and simulated scenes. J. Vis. 16(11), 2–2 (2016)

    Google Scholar 

  47. Weiss, D., Witzel, C., Gegenfurtner, K.: Determinants of colour constancy and the blue bias. i-Perception. 8(6), 2041669517739635 (2017)

    Google Scholar 

  48. Pearce, B., Crichton, S., Mackiewicz, M., Finlayson, G.D., Hurlbert, A.: Chromatic illumination discrimination ability reveals that human colour constancy is optimised for blue daylight illuminations. PLoS One. 9(2), (2014)

    Google Scholar 

  49. Bartels, A., Zeki, S.: The architecture of the colour Centre in the human visual brain: new results and a review. Eur. J. Neurosci. 12(1), 172–193 (2000)

    Google Scholar 

  50. Beauchamp, M.S., Haxby, J.V., Jennings, J.E., DeYoe, E.A.: An fMRI version of the Farnsworth–Munsell 100-hue test reveals multiple color-selective areas in human ventral occipitotemporal cortex. Cereb. Cortex. 9(3), 257–263 (1999)

    Google Scholar 

  51. Engel, S.A., Glover, G.H., Wandell, B.A.: Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cereb. Cortex. 7(2), 181–192 (1997)

    Google Scholar 

  52. Zeki, S.M.: Colour coding in rhesus monkey prestriate cortex. Brain Res. 53(2), 422–427 (1973)

    Google Scholar 

  53. Zeki, S.: Colour coding in the cerebral cortex: the reaction of cells in monkey visual cortex to wavelengths and colours. Neuroscience. 9(4), 741–765 (1983)

    Google Scholar 

  54. Komatsu, H.: Mechanisms of central color vision. Curr. Opin. Neurobiol. 8(4), 503–508 (1998)

    Google Scholar 

  55. Schein, S.J., Desimone, R.: Spectral properties of V4 neurons in the macaque. J. Neurosci. 10(10), 3369–3389 (1990)

    Google Scholar 

  56. Conway, B.R., Eskew Jr., R.T., Martin, P.R., Stockman, A.: A tour of contemporary color vision research. Vis. Res. 151, 2–6 (2018)

    Google Scholar 

  57. Bannert, M.M., Bartels, A.: Invariance of surface color representations across illuminant changes in the human cortex. NeuroImage. 158, 356–370 (2017)

    Google Scholar 

  58. von Kries J. Chromatic Adaptation, Festschrift der Albrecht-Ludwig-Universitat; 1902

    Google Scholar 

  59. Webster, M.A., Mollon, J.: Adaptation and the color statistics of natural images. Vis. Res. 37(23), 3283–3298 (1997)

    Google Scholar 

  60. Land, E.H.: The retinex theory of color vision. Sci. Am. 237(6), 108–129 (1977)

    Google Scholar 

  61. Brainard, D.H., Wandell, B.A.: Analysis of the retinex theory of color vision. JOSA A. 3(10), 1651–1661 (1986)

    ADS  Google Scholar 

  62. Brainard, D.H., Brunt, W.A., Speigle, J.M.: Color constancy in the nearly natural image. 1. Asymmetric matches. JOSA A. 14(9), 2091–2110 (1997)

    ADS  Google Scholar 

  63. Brainard, D.H., Freeman, W.T.: Bayesian color constancy. JOSA A. 14(7), 1393–1411 (1997)

    ADS  Google Scholar 

  64. Brainard, D.H., Longère, P., Delahunt, P.B., Freeman, W.T., Kraft, J.M., Xiao, B.: Bayesian model of human color constancy. J. Vis. 6(11), 10–10 (2006)

    Google Scholar 

  65. Brainard D, Gazzaniga M. Bayesian approaches to color vision. The cognitive neurosciences. 2009.;4 MIT Press, Cambridge, MA:395–408

    Google Scholar 

  66. Lafer-Sousa, R., Hermann, K.L., Conway, B.R.: Striking individual differences in color perception uncovered by ‘the dress’ photograph. Curr. Biol. 25(13), R545–R546 (2015)

    Google Scholar 

  67. Brainard, D.H., Hurlbert, A.C.: Colour vision: understanding# TheDress. Curr. Biol. 25(13), R551–R554 (2015)

    Google Scholar 

  68. Dixon, E.L., Shapiro, A.G.: Spatial filtering, color constancy, and the color-changing dress. J. Vis. 17(3), 7–7 (2017)

    Google Scholar 

  69. Gegenfurtner, K.R., Bloj, M., Toscani, M.: The many colours of ‘the dress’. Curr. Biol. 25(13), R543–R544 (2015)

    Google Scholar 

  70. Wallisch, P.: Illumination assumptions account for individual differences in the perceptual interpretation of a profoundly ambiguous stimulus in the color domain:“the dress”. J. Vis. 17(4), 5–5 (2017)

    Google Scholar 

  71. Uchikawa, K., Morimoto, T., Matsumoto, T.: Understanding individual differences in color appearance of “# TheDress” based on the optimal color hypothesis. J. Vis. 17(8), 10–10 (2017)

    Google Scholar 

  72. Lafer-Sousa, R., Conway, B.R.: # TheDress: categorical perception of an ambiguous color image. J. Vis. 17(12), 25–25 (2017)

    Google Scholar 

  73. Zhao, S., Jakob, W., Marschner, S., Bala, K.: Building volumetric appearance models of fabric using micro CT imaging. ACM Trans. Graph. (TOG). 30(4), 1–10 (2011)

    Google Scholar 

  74. Lafer-Sousa, R., Liu, Y.O., Lafer-Sousa, L., Wiest, M.C., Conway, B.R.: Color tuning in alert macaque V1 assessed with fMRI and single-unit recording shows a bias toward daylight colors. JOSA A. 29(5), 657–670 (2012)

    ADS  Google Scholar 

  75. Buchsbaum, G.: A spatial processor model for object colour perception. J. Frankl. Inst. 310(1), 1–26 (1980)

    Google Scholar 

  76. Funt, B., Shi, L.: The rehabilitation of maxrgb. In: Color and Imaging Conference, vol. 1, pp. 256–259. Society for Imaging Science and Technology (2010)

    Google Scholar 

  77. Finlayson, G.D., Hordley, S.D., Hubel, P.M.: Color by correlation: a simple, unifying framework for color constancy. IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1209–1221 (2001)

    Google Scholar 

  78. Van De Weijer, J., Gevers, T., Gijsenij, A.: Edge-based color constancy. IEEE Trans. Image Process. 16(9), 2207–2214 (2007)

    ADS  MathSciNet  Google Scholar 

  79. Chakrabarti, A., Hirakawa, K., Zickler, T.: Color constancy with spatio-spectral statistics. IEEE Trans. Pattern Anal. Mach. Intell. 34(8), 1509–1519 (2011)

    Google Scholar 

  80. Forsyth, D.A.: A novel algorithm for color constancy. Int. J. Comput. Vis. 5(1), 5–35 (1990)

    Google Scholar 

  81. Rosenberg, C., Ladsariya, A., Minka, T.: Bayesian color constancy with non-gaussian models. In: Advances in Neural Information Processing Systems, pp. 1595–1602 (2004)

    Google Scholar 

  82. Gehler, P.V., Rother, C., Blake, A., Minka, T., Sharp, T.: Bayesian color constancy revisited. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2008)

    Google Scholar 

  83. Barron, J.T., Tsai, Y.T.: Fast fourier color constancy. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–894 (2017)

    Google Scholar 

  84. Bianco, S., Ciocca, G., Cusano, C., Schettini, R.: Classification-based color constancy. International Conference on Advances in Visual Information Systems. Springer. 104–113 (2008)

    Google Scholar 

  85. Gijsenij, A., Gevers, T.: Color constancy by local averaging. In: 14th International Conference of Image Analysis and Processing-Workshops (ICIAPW 2007), pp. 171–174. IEEE (2007)

    Google Scholar 

  86. Van De Weijer, J., Schmid, C., Verbeek, J.: Using high-level visual information for color constancy. In: 2007 IEEE 11th International Conference on Computer Vision, pp. 1–8. IEEE (2007)

    Google Scholar 

  87. Gijsenij, A., Gevers, T.: Color constancy using natural image statistics and scene semantics. IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 687–698 (2010)

    Google Scholar 

  88. Bianco, S., Schettini, R.: Color constancy using faces. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 65–72. IEEE (2012)

    Google Scholar 

  89. Gao, S., Yang, K., Li, C., Li, Y.: A color constancy model with double-opponency mechanisms. Proceedings of the IEEE international conference on computer vision. 929–936 (2013)

    Google Scholar 

  90. Bianco, S., Cusano, C., Schettini, R.: Color constancy using CNNs. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 81–89 (2015)

    Google Scholar 

  91. Lou, Z., Gevers, T., Hu, N., Lucassen, M.P.: Color Constancy by deep learning. In: Xianghua Xie, M.W.J., Tam, G.K.L. (eds.) Proceedings of the British Machine Vision Conference (BMVC), pp. 76.1–76.12. BMVA Press (2015). https://doi.org/10.5244/C.29.76

  92. Shi, W., Loy, C.C., Tang, X.: Deep specialized network for illuminant estimation. European Conference on Computer Vision. Springer. 371–387 (2016)

    Google Scholar 

  93. Hu, Y., Wang, B., Lin, S.: Fc4: Fully convolutional color constancy with confidence-weighted pooling. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4085–4094 (2017)

    Google Scholar 

  94. Bianco, S., Cusano, C., Schettini, R.: Single and multiple illuminant estimation using convolutional neural networks. IEEE Trans. Image Process. 26(9), 4347–4362 (2017)

    ADS  MathSciNet  MATH  Google Scholar 

  95. Qian, Y., Chen, K., Nikkanen, J., Kamarainen, J.K., Matas, J.: Recurrent color constancy. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5458–5466 (2017)

    Google Scholar 

  96. Bianco, S., Cusano, C.: Quasi-unsupervised color constancy. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 12212–12221 (2019)

    Google Scholar 

  97. Afifi, M., Price, B., Cohen, S., Brown, M.S.: When color constancy goes wrong: correcting improperly white-balanced images. Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 1535–1544 (2019)

    Google Scholar 

  98. Brainard, D., Radonjić, A.: Color constancy. In: The New Visual Neurosciences, pp. 545–556. MIT Press (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, American University, Washington, DC, USA

    Bei Xiao

Authors
  1. Bei Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bei Xiao .

Editor information

Editors and Affiliations

  1. Color Science & Imaging Lab, North Carolina State Univ, Raleigh, NC, USA

    Renzo Shamey

Section Editor information

  1. Color Science, NC State University, Raleigh, NC, USA

    Rolf G. Kuehni

  2. Color Research & Application, Pennsville, NJ, USA

    Rolf G. Kuehni

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Science+Business Media LLC

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Xiao, B. (2020). Color Constancy. In: Shamey, R. (eds) Encyclopedia of Color Science and Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27851-8_266-2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-27851-8_266-2

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27851-8

  • Online ISBN: 978-3-642-27851-8

  • eBook Packages: Springer Reference Physics and AstronomyReference Module Physical and Materials ScienceReference Module Chemistry, Materials and Physics

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Color Constancy
    Published:
    16 July 2020

    DOI: https://doi.org/10.1007/978-3-642-27851-8_266-2

  2. Original

    Color Constancy
    Published:
    03 October 2015

    DOI: https://doi.org/10.1007/978-3-642-27851-8_266-1

Search

Navigation