Colour Spaces for Colour Transfer

  • Erik Reinhard
  • Tania Pouli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6626)


Colour transfer algorithms aim to apply a colour palette, mood or style from one image to another, operating either in a three-dimensional colour space, or splitting the problem into three simpler one-dimensional problems. The latter class of algorithms simply treats each of the three dimensions independently, whether justified or not. Although they rarely introduce spatial artefacts, the quality of the results depends on how the problem was split into three sub-problems, i.e. which colour space was chosen. Generally, the assumption is made that a decorrelated colour space would perform best, as decorrelation makes the three colour channels semi-independent (decorrelation is a weaker property than independence). However, such spaces are only decorrelated for well-chosen image ensembles. For individual images, this property may not hold. In this work, the connection between the natural statistics of colour images and the ability of existing colour transfer algorithms to produce plausible results is investigated. This work aims to provide a better understanding of the performance of different colour spaces in the context of colour transfer.


Colour Transfer Colour Spaces Correlation 


  1. 1.
    Abadpour, A., Kasaei, S.: A fast and efficient fuzzy color transfer method. In: Proceedings of the 4th IEEE International Symposium on Signal Processing and Information Technology, pp. 491–494 (2004)Google Scholar
  2. 2.
    Abadpour, A., Kasaei, S.: An efficient PCA-based color transfer method. Journal of Visual Communication and Image Representation 18, 15–34 (2007)CrossRefGoogle Scholar
  3. 3.
    An, X., Pellacini, F.: User controllable color transfer. Computer Graphics Forum 29, 263–271 (2010)CrossRefGoogle Scholar
  4. 4.
    Chang, Y., Uchikawa, K., Saito, S.: Example-based color stylization based on categorical perception. In: Proceedings of the 1st Symposium on Applied Perception in Graphics and Visualization (APGV 2004), pp. 91–98 (2004)Google Scholar
  5. 5.
    Greenfield, G., House, D.: Image recoloring induced by palette color associations. Journal of WSCG 11(1), 189–196 (2003)Google Scholar
  6. 6.
    Grundland, M., Dodgson, N.: The decolorize algorithm for contrast enhancing, color to grayscale conversion. Tech. Rep. UCAM-CL-TR-649, University of Cambridge (2005)Google Scholar
  7. 7.
    Kotera, H.: A scene-referred color transfer for pleasant imaging on display. In: IEEE International Conference on Image Processing, vol. 2, pp. 5–8 (2005)Google Scholar
  8. 8.
    Kotera, H., Morimoto, T., Saito, R.: Object-oriented color matching by image clustering. In: Proceedings of the 6th Color Imaging Conference, pp. 154–158 (1998)Google Scholar
  9. 9.
    Kumar, R., Mitra, S.K.: Motion estimation based color transfer and its application to color video compression. Pattern Analysis and Applications 11(2), 131–139 (2007)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Transactions on Graphics 24(3), 689–694 (2004)CrossRefGoogle Scholar
  11. 11.
    Li, Z., Jing, Z., Yang, X., Sun, S.: Color transfer based remote sensing image fusion using non-separable wavelet frame transform. Pattern Recognition Letters 26, 2006–2014 (2005)CrossRefGoogle Scholar
  12. 12.
    Luan, Q., Wen, F., Xu, Y.Q.: Color transfer brush. In: Proceedings of Pacific Graphics, pp. 465–468 (2007)Google Scholar
  13. 13.
    Morovic, J., Sun, P.L.: Accurate 3D image colour histogram transformation. Pattern Recognition Letters 24, 1725–1735 (2003)CrossRefGoogle Scholar
  14. 14.
    Neumann, L., Neumann, A.: Color style transfer techniques using hue, lightness and saturation histogram matching. In: Computational Aesthetics in Graphics, Visualization and Imaging, pp. 111–122 (2005)Google Scholar
  15. 15.
    Pitié, F., Kokaram, A., Dahyot, R.: N-dimensional probability density function transfer and its application to colour transfer. In: ICCV 2005: Proceedings of the 2005 IEEE International Conference on Computer Vision, vol. 2, pp. 1434–1439 (2005)Google Scholar
  16. 16.
    Pitié, F., Kokaram, A., Dahyot, R.: Automated colour grading using colour distribution transfer. Computer Vision and Image Understanding 107(2), 1434–1439 (2007)Google Scholar
  17. 17.
    Pouli, T., Reinhard, E.: Progressive histogram reshaping for creative color transfer and tone reproduction. In: NPAR 2010: Proceedings of the 8th International Symposium on Non-Photorealistic Animation and Rendering, pp. 81–90 (2010)Google Scholar
  18. 18.
    Pouli, T., Reinhard, E.: Progressive color transfer for images of arbitrary dynamic range. Computers and Graphics 35(1), 67–80 (2011)CrossRefGoogle Scholar
  19. 19.
    Reinhard, E., Ashikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Computer Graphics and Applications 21, 34–41 (2001)CrossRefGoogle Scholar
  20. 20.
    Reinhard, E., Shirley, P., Ashikhmin, M., Troscianko, T.: Second order image statistics in computer graphics. In: Proceedings of the 1st Symposium on Applied Perception in Graphics and Visualization, pp. 99–106 (2004)Google Scholar
  21. 21.
    Reinhard, E., Akyüz, A.O., Colbert, M., Hughes, C.E., O’Connor, M.: Real-time color blending of rendered and captured video. In: Interservice/Industry Training, Simulation and Education Conference (2004)Google Scholar
  22. 22.
    Reinhard, E., Khan, E.A., Akyüz, A.O., Johnson, G.M.: Color Imaging: Fundamentals and Applications. A K Peters, Wellesley (2008)Google Scholar
  23. 23.
    Ruderman, D., Cronin, T., Chiao, C.: Statistics of cone responses to natural images: implications for visual coding. Journal of the Optical Society of America A 15(8), 2036–2045 (1998)CrossRefGoogle Scholar
  24. 24.
    Tai, Y., Jia, J., Tang, C.: Local color transfer via probabilistic segmentation by expectation-maximization. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. 1, pp. 747–754 (2005)Google Scholar
  25. 25.
    Toet, A.: Natural colour mapping for multiband nightvision imagery. Information Fusion 4, 155–166 (2003)CrossRefGoogle Scholar
  26. 26.
    Wang, C.M., Huang, Y.H., Huang, M.L.: An effective algorithm for image sequence color transfer. Mathematical and Computer Modelling 44, 608–627 (2006)CrossRefzbMATHGoogle Scholar
  27. 27.
    Wang, L., Zhao, Y., Jin, W., Shi, S., Wang, S.: Real-time color transfer system for low-light level visible and infrared images in YUV color space. In: Proceedings of the SPIE, vol. 6567, p. 65671G (2007)Google Scholar
  28. 28.
    Wen, C.L., Hsieh, C.H., Chen, B.Y., Ming, O.: Example-based multiple local color transfer by strokes. Computer Graphics Forum 27(7), 1762–1765 (2008)CrossRefGoogle Scholar
  29. 29.
    Wyszecki, G., Stiles, W.S.: Color science: Concepts and methods, quantitative data and formulae, 2nd edn. John Wiley and Sons, New York (2000)Google Scholar
  30. 30.
    Xiang, Y., Zou, B., Li, H.: Selective color transfer with multi-source images. Pattern Recognition Letters 30, 682–689 (2009)CrossRefGoogle Scholar
  31. 31.
    Xiao, X., Ma, L.: Color transfer in correlated color space. In: VRCIA 2006: Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and its Applications, pp. 305–309 (2006)Google Scholar
  32. 32.
    Xiao, X., Ma, L.: Gradient-preserving color transfer. Computer Graphics Forum 28, 1879–1886 (2009)CrossRefGoogle Scholar
  33. 33.
    Xu, S., Zhang, Y., Zhang, S., Ye, X.: Uniform color transfer. In: IEEE International Conference on Image Processing, pp. III-940–III-943 (2005)Google Scholar
  34. 34.
    Yin, J., Cooperstock, J.R.: Color correction methods with applications to digital projection environments. Journal of the WSCG 12(1-3) (2004)Google Scholar
  35. 35.
    Zhao, Y., Wang, L., Jin, W., Shi, S.: Colorizing biomedical images based on color transfer. In: IEEE/ICME International Conference on Complex Medical Engineering, pp. 820–823 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Erik Reinhard
    • 1
  • Tania Pouli
    • 1
  1. 1.Dept. of Computer ScienceUniversity of BristolUK

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