Performance Comparison of Techniques for Approximating Image-Based Lighting by Directional Light Sources

  • Claus B. Madsen
  • Rune E. Laursen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


Image-Based Lighting (IBL) has become a very popular approach in computer graphics. In essence IBL is based on capturing the illumination conditions in a scene in an omni-directional image, called a light probe image. Using the illumination information from such an image virtual objects can be rendered with consistent shading including global illumination effects such as color bleeding.

Rendering with light probe illumination is extremely time consuming. Therefore a range of techniques exist for approximating the incident radiance described in a light probe image by a finite number of directional light sources. We describe two such techniques from the literature and perform a comparative evaluation of them in terms of how well they each approximate the final irradiance. We demonstrate that there is significant difference in the performance of the two techniques.


Augmented Reality Image-Based Lighting median cut irradiance real-time rendering directional light sources 


  1. 1.
    M., O.M.: Image-based modelling and rendering: A survey. RITA - Revista de Informatica Teorica a Aplicada 9(2), 37–66 (2002)Google Scholar
  2. 2.
    Debevec, P.: Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. In: Proceedings: SIGGRAPH 1998, Orlando, Florida, USA (July 1998)Google Scholar
  3. 3.
    Debevec, P., et al.: Homepage of HDRShop,
  4. 4.
    Debevec, P., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: Proceedings: SIGGRAPH 1997, Los Angeles, CA, USA (August 1997)Google Scholar
  5. 5.
    Debevec, P.: Tutorial: Image-based lighting. IEEE Computer Graphics and Applications, 26–34 (March/April 2002)Google Scholar
  6. 6.
    Gibson, S., Cook, J., Howard, T., Hubbold, R.: Rapic shadow generation in real-world lighting environments. In: Proceedings: EuroGraphics Symposium on Rendering, Leuwen, Belgium (June 2003)Google Scholar
  7. 7.
    Yu, Y., Malik, J.: Recovering photometric properties of architectural scenes from photographs. In: Proceedings: SIGGRAPH 1998, Orlando, Florida, USA, July 1998, pp. 207–217 (1998)Google Scholar
  8. 8.
    Yu, Y., Debevec, P., Malik, J., Hawkins, T.: Inverse global illumination: Recovering reflectance models of real scenes from photographs. In: Proceedings: SIGGRAPH 1999, Los Angeles, California, USA, August 1999, pp. 215–224 (1999)Google Scholar
  9. 9.
    Jacobs, K., Loscos, C.: State of the art report on classification of illumination methods for mixed reality. In: EUROGRAPHICS, Grenoble, France (Sep. 2004),
  10. 10.
    Debevec, P.: Homepage of Paul Debevec,
  11. 11.
    Phar, M., Humphreys, G.: Physicaly Based Rendering – From Theory to Implementation. Elsevier, Amsterdam (2004)Google Scholar
  12. 12.
    Jensen, H.W.: Realistic Image Synthesis Using Photon Mapping. A.K. Peters, Wellesley (2001)zbMATHGoogle Scholar
  13. 13.
    Cohen, J.M., Debevec, P.: The LightGen HDRShop plugin (2001),
  14. 14.
    Debevec, P.: A median cut algorithm for light probe sampling (Poster abstract). In: Proceedings: SIGGRAPH 2005, Los Angeles, California, USA (August 2005)Google Scholar
  15. 15.
    Madsen, C.B., Sørensen, M.K.D., Vittrup, M.: Estimating positions and radiances of a small number of light sources for real-time image-based lighting. In: Proceedings: Annual Conference of the European Association for Computer Graphics, EUROGRAPHICS 2003, Granada, Spain, September 2003, pp. 37–44 (2003)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Claus B. Madsen
    • 1
  • Rune E. Laursen
    • 1
  1. 1.Laboratory of Computer Vision and Media Technology, Aalborg UniversityDenmark

Personalised recommendations