Spatio-temporal Tone Mapping Operator Based on a Retina Model

  • Alexandre Benoit
  • David Alleysson
  • Jeanny Herault
  • Patrick Le Callet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5646)


From moonlight to bright sun shine, real world visual scenes contain a very wide range of luminance; they are said to be High Dynamic Range (HDR). Our visual system is well adapted to explore and analyze such a variable visual content. It is now possible to acquire such HDR contents with digital cameras; however it is not possible to render them all on standard displays, which have only Low Dynamic Range (LDR) capabilities. This rendering usually generates bad exposure or loss of information. It is necessary to develop locally adaptive Tone Mapping Operators (TMO) to compress a HDR content to a LDR one and keep as much information as possible. The human retina is known to perform such a task to overcome the limited range of values which can be coded by neurons. The purpose of this paper is to present a TMO inspired from the retina properties. The presented biological model allows reliable dynamic range compression with natural color constancy properties. Moreover, its non-separable spatio-temporal filter enhances HDR video content processing with an added temporal constancy.


High Dynamic Range compression tone mapping retina model color constancy video sequence tone mapping 


  1. 1.
    Hérault, J., Durette, B.: Modeling Visual Perception for Image Processing. In: Sandoval, F., Prieto, A.G., Cabestany, J., Graña, M., et al. (eds.) IWANN 2007. LNCS, vol. 4507, pp. 662–675. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  2. 2.
    Reinhard, E., Ward, G., Debevec, P., Pattanaik, S.: High Dynamic Range Imaging: Acquisition, Display, and Image Based Lighting. Morgan Kaufmann, San Francisco (2005)Google Scholar
  3. 3.
    Ward, G.: The RADIANCE Lighting Simulation and Rendering System. In: Computer Graphics Proceedings, Annual Conference Series (1994)Google Scholar
  4. 4.
    Hoefflinger, B.: High-Dynamic-Range (HDR) VisionMicroelectronics, Image Processing. In: Computer Graphics. Springer, Heidelberg (2007)Google Scholar
  5. 5.
    Ahmet, O.A., Erik, R.: Perceptual Evaluation of Tone Reproduction Operators Using the Cornsweet-Craik-O’Brien Illusion. ACM Transactions on Applied Perception 4(4), 1–29 (2008)Google Scholar
  6. 6.
    Jiangtao, K., Hiroshi, Y., Changmeng, L., Garrett, M.J., Mark, F.D.: Evaluating HDR rendering algorithms. ACM Trans. Appl. Percept. 4(2), 9 (2007)CrossRefGoogle Scholar
  7. 7.
    Johnson, G.: Cares and concerns of CIE TC8-08: Spatial appearance modeling and HDR rendering. In: SPIE proceedings series, Image quality and system performance, pp. 148–156 (2005)Google Scholar
  8. 8.
    Aydin, T.O., Mantiuk, R., Myszkowski, K., Seidel, H.-P.: Dynamic Range Independent Image Quality Assessment. ACM Transactions on Graphics (Proc. of SIGGRAPH 2008) 27(3) (to appear)Google Scholar
  9. 9.
    Kuang, J., Yamaguchi, H., Liu, C., Johnson, G.M., Fairchild, M.D.: Evaluating HDR rendering algorithms. ACM Transactions on Applied Perception 4, Article 9 (2007)Google Scholar
  10. 10.
    Meylan, L., Alleysson, D., Susstrunk, S.: A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images. Journal of the Optical Society of America A (JOSA A) 24(9), 2807–2816 (2007)CrossRefGoogle Scholar
  11. 11.
    Smirnakis, S.M., Berry, M.J., Warland, D.K., Bialek, W., Meister, M.: Adaptation of Retinal Processing to Image Contrast and Spatial Scale. Nature 386, 69–73 (1997)CrossRefGoogle Scholar
  12. 12.
    Chaix de Lavarène, B., Alleysson, D., Hérault, J.: Practical Implementation of LMMSE Demosaicing Using Luminance and Chrominance Spaces. Computer Vision and Image Understanding 107(1), 3–13 (2007)CrossRefGoogle Scholar
  13. 13.
    Mantiuk, R., Daly, S., Kerofsky, L.: Display Adaptive Tone Mapping. ACM Transactions on Graphics (Proc. of SIGGRAPH 2008) 27(3) (to appear)Google Scholar
  14. 14.
    Yoshida, A., Blanz, V., Myszkowski, K., Seidel, H.: Perceptual Evaluation of Tone Mapping Operators with Real-World Sceness. In: Rogowitz, B.E., Pappas, T.N., Daly, S.J. (eds.) Human Vision and Electronic Imaging X, IS&T/SPIE’s 17th Annual Symposium on Electronic Imaging, pp. 192–203. SPIE, San Jose (2005)CrossRefGoogle Scholar
  15. 15.
    Mantiuk, R., Myszkowski, K., Seidel, H.-P.: A Perceptual Framework for Contrast Processing of High Dynamic Range Images (revised and extended version). ACM Transactions on Applied Perception 3(3), 286–308 (2006)CrossRefGoogle Scholar
  16. 16.
  17. 17.
    Didyk, P., Mantiuk, R., Hein, M., Seidel, H.-P.: Enhancement of Bright Video Features for HDR Displays. In: Computer Graphics Forum (Proc. of EGSR 2008) (2008) (to appear)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Alexandre Benoit
    • 1
  • David Alleysson
    • 2
  • Jeanny Herault
    • 3
  • Patrick Le Callet
    • 4
  1. 1.LISTIC 74940 Annecy le VieuxFrance
  2. 2.LPNC 38040 GrenobleFrance
  3. 3.Gipsa Lab 38402 GrenobleFrance
  4. 4.IRCCyN 44321 NantesFrance

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