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The Visual Computer

, Volume 23, Issue 7, pp 467–478 | Cite as

A framework for inverse tone mapping

  • Francesco Banterle
  • Patrick Ledda
  • Kurt Debattista
  • Alan Chalmers
  • Marina Bloj
Original Article

Abstract

In recent years many tone mapping operators (TMOs) have been presented in order to display high dynamic range images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The inverse of tone mapping, inverse tone mapping, expands a low dynamic range image (LDRI) into an HDRI. HDRIs contain a broader range of physical values that can be perceived by the human visual system. We propose a new framework that approximates a solution to this problem. Our framework uses importance sampling of light sources to find the areas considered to be of high luminance and subsequently applies density estimation to generate an expand map in order to extend the range in the high luminance areas using an inverse tone mapping operator. The majority of today’s media is stored in the low dynamic range. Inverse tone mapping operators (iTMOs) could thus potentially revive all of this content for use in high dynamic range display and image based lighting (IBL). Moreover, we show another application that benefits quick capture of HDRIs for use in IBL.

Keywords

Inverse tone mapping Image enhancement High dynamic range imaging Image editing Image based lighting 

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References

  1. 1.
    Agarwal, S., Ramamoorthi, R., Belongie, S., Jensen, H.W.: Structured importance sampling of environment maps. In: SIGGRAPH ’03: ACM SIGGRAPH 2003 Papers, pp. 605–612. ACM, New York (2003)Google Scholar
  2. 2.
    Bennett, E.P., McMillan, L.: Video enhancement using per-pixel virtual exposures. ACM Trans. Graph. 24(3), 845–852 (2005)CrossRefGoogle Scholar
  3. 3.
    Brightside Technologies: http://www.brightsidetech.com. Cited (2005)Google Scholar
  4. 4.
    Daly, S.: The visible differences predictor: an algorithm for the assessment of image fidelity. MIT Press, Cambridge, MA (1993)Google Scholar
  5. 5.
    Debevec, P.E.: A median cut algorithm for light probe sampling. In: ACM SIGGRAPH 2005 Posters (2005)Google Scholar
  6. 6.
    Debevec, P.E., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: SIGGRAPH ’97: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, pp. 369–378. ACM/Addison-Wesley, New York (1997)Google Scholar
  7. 7.
    Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. Wiley Interscience, New York (2001)zbMATHGoogle Scholar
  8. 8.
    Jensen, H.W.: Realistic image synthesis using photon mapping. Peters, Natick, MA (2001)zbMATHGoogle Scholar
  9. 9.
    Kang, S.B., Uyttendaele, M., Winder, S., Szeliski, R.: High dynamic range video. ACM Trans. Graph. 22(3), 319–325 (2003)CrossRefGoogle Scholar
  10. 10.
    Landis, H.: Production-ready global illumination. In: ACM SIGGRAPH Course Notes 16 (2002)Google Scholar
  11. 11.
    Ledda, P., Chalmers, A., Troscianko, T., Seetzen, H.: Evaluation of tone mapping operators using a high dynamic range display. ACM Trans. Graph. 24(3), 640–648 (2005)CrossRefGoogle Scholar
  12. 12.
    Mantiuk, R., Daly, S., Myszkowski, K., Seidel, H.-P.: Predicting visible differences in high dynamic range images: model and its calibration. In: Rogowitz, B.E., Pappas, T.N., Daly, S.J. (eds.) Human Vision and Electronic Imaging X, IS&T/SPIE 17th Annual Symposium on Electronic Imaging, vol. 5666, pp. 204–214 (2005)Google Scholar
  13. 13.
    Mantiuk, R., Myszkowski, K., Seidel, H.-P.: Visible difference predicator for high dynamic range images. In: Proceedings of IEEE International Conference on Systems, Man and Cybernetics, pp. 2763–2769 (2004)Google Scholar
  14. 14.
    Meylan, L., Daly, S., Süsstrunk, S.: The reproduction of specular highlights on high dynamic range displays. In: IS&T/SID 14th Color Imaging Conference (2006)Google Scholar
  15. 15.
    Ostromoukhov, V., Donohue, C., Jodoin, P.-M.: Fast hierarchical importance sampling with blue noise properties. ACM Trans. Graph. 23(3), 488–495 (2004)CrossRefGoogle Scholar
  16. 16.
    PanoScan: http://www.panoscan.com. Cited (2007)Google Scholar
  17. 17.
    Pavicic, M.J.: Convenient Anti-Aliasing Filters that Minimize Bumpy Sampling. Morgan Kaufmann, San Francisco (1990)Google Scholar
  18. 18.
    Pharr, M., Humphreys, G.: Improved Infinite Area Light Source Sampling. Morgan Kaufmann, San Francisco (2004)Google Scholar
  19. 19.
    Reinhard, E.: Parameter estimation for photographic tone reproduction. J. Graph. Tools 7(1), 45–52 (2002)zbMATHMathSciNetGoogle Scholar
  20. 20.
    Reinhard, E., Stark, M., Shirley, P., Ferwerda, J.: Photographic tone reproduction for digital images. ACM Trans. Graph. 21(3), 267–276 (2002)CrossRefGoogle Scholar
  21. 21.
    Reinhard, E., Ward, G., Pattanaik, S., Debevec, P.: High Dynamic Range Imaging: Acquisition, Display and Image-Based Lighting. Morgan Kaufmann, San Francisco (2005)Google Scholar
  22. 22.
    Seetzen, H., Heidrich, W., Stuerzlinger, W., Ward, G., Whitehead, L., Trentacoste, M., Ghosh, A., Vorozcovs, A.: High dynamic range display systems. ACM Trans. Graph. 23(3), 760–768 (2004)CrossRefGoogle Scholar
  23. 23.
    Smith, K., Krawczyk, G., Myszkowski, K., Seidel, H.-P.: Beyond tone mapping: enhanced depiction of tone mapped HDR images. Comput. Graph. Forum 25(3), 427–438 (2006)CrossRefGoogle Scholar
  24. 24.
    SpheronVR. http://www.spheron.com. Cited (2007)Google Scholar
  25. 25.
    VDP-HDR. http://www.mpi-sb.mpg.de/resources/hdr/vdp. Cited (2007)Google Scholar
  26. 26.
    Ward, G., Simmons, M.: JPEG-HDR: A backwards-compatible, high dynamic range extension to JPEG. In: Proceedings of the 13th Color Imaging Conference (2005)Google Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Francesco Banterle
    • 1
  • Patrick Ledda
    • 1
  • Kurt Debattista
    • 1
  • Alan Chalmers
    • 1
  • Marina Bloj
    • 2
  1. 1.Warwick Digital LaboratoryUniversity of WarwickCoventryUK
  2. 2.Optometry DepartmentUniversity of BradfordBradfordUK

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