Computational Photography: Epsilon to Coded Photography

  • Ramesh Raskar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5416)


Computational photography combines plentiful computing, digital sensors, modern optics, actuators, and smart lights to escape the limitations of traditional cameras, enables novel imaging applications and simplifies many computer vision tasks. However, a majority of current Computational photography methods involves taking multiple sequential photos by changing scene parameters and fusing the photos to create a richer representation. Epsilon photography is concerned with synthesizing omnipictures and proceeds by multiple capture single image paradigm (MCSI).The goal of Coded computational photography is to modify the optics, illumination or sensors at the time of capture so that the scene properties are encoded in a single (or a few) photographs. We describe several applications of coding exposure, aperture, illumination and sensing and describe emerging techniques to recover scene parameters from coded photographs.


Digital photography Fourier transform Fourier optics Optical heterodyning Coded aperture imaging digital refocusing plenoptic camera 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Raskar, R., Tan, K., Feris, R., Yu, J., Turk, M.: Non-photorealistic Camera: Depth Edge Detection and Stylized Rendering Using a Multi-Flash Camera. In: Proc. ACM SIGGRAPH (2004)Google Scholar
  2. 2.
    Tumblin, J., Agrawal, A., Raskar, R.: Why I want a Gradient Camera. IEEE Computer Vision and Pattern Recognition (2005)Google Scholar
  3. 3.
    Raskar, R., Agrawal, A., Tumblin, J.: Coded exposure photography: motion deblurring using fluttered shutter. ACM Transactions on Graphics 25(3), 795–804 (2006)CrossRefGoogle Scholar
  4. 4.
    Veeraraghavan, A., Raskar, R., Agrawal, A., Mohan, A., Tumblin, J.: Dappled Photography: Mask-Enhanced Cameras for Heterodyned Light Fields and Coded Aperture Refocusing. In: Proc. ACM SIGGRAPH (2007)Google Scholar
  5. 5.
    Nayar, S.K., Narasimhan, S.G.: Assorted Pixels: Multi-Sampled Imaging With Structural Models. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 636–652. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  6. 6.
    Debevec, M.: Recovering high dynamic range radiance maps from photographs. In: Proc. ACM SIGGRAPH (1997)Google Scholar
  7. 7.
    Mann, P.: Being ’undigital’ with digital cameras: Extending dynamic range by combining differently exposed pictures. In: Proc. Imaging Science and Technology 46th ann. conference (1995)Google Scholar
  8. 8.
    Morgan, M., Matusik, P., Hughes, D.: Defocus Video Matting. ACM Transactions on Graphics 24(3) (July 2005) (Proceedings of ACM SIGGRAPH 2005)Google Scholar
  9. 9.
    Adelson, E.H., Wang, J.Y.A.: Single Lens Stereo with a Plenoptic Camera. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2) (February 1992)Google Scholar
  10. 10.
    Ren, N.: Fourier Slice Photography. In: ACM SIGGRAPH (2005)Google Scholar
  11. 11.
    Morimura: Imaging method for a wide dynamic range and an imaging device for a wide dynamic range. U.S. Patent 5455621 (October 1993)Google Scholar
  12. 12.
    Levoy, M., Hanrahan, P.: Light field rendering. In: ACM SIGGRAPH, pp. 31–42 (1996)Google Scholar
  13. 13.
    Gortler, S.J., Grzeszczuk, R., Szeliski, R., Cohen, M.F.: The Lumigraph. In: ACM SIGGRAPH, pp. 43–54 (1996)Google Scholar
  14. 14.
    Dowski Jr., E.R., Cathey, W.T.: Extended depth of field through wave-front coding. Applied Optics 34(11), 1859–1866 (1995)CrossRefGoogle Scholar
  15. 15.
    Georgiev, T., Zheng, C., Nayar, S., Salesin, D., Curless, B., Intwala, C.: Spatio-angular Resolution Trade-Offs in Integral Photography. In: Proceedings of Eurographics Symposium on Rendering (2006)Google Scholar
  16. 16.
    Tumblin, J.: Slides on the Photographic Signal and Film-like Photography. In: Course 3: Computational Photography, ACM SIGGRAPH (2005),
  17. 17.
  18. 18.
    Bidirectional reflectance distribution function,
  19. 19.
  20. 20.
    Programmable Interface Controller,
  21. 21.

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ramesh Raskar
    • 1
  1. 1.Media LaboratoryMassachusetts Institute of TechnologyCambridgeUSA

Personalised recommendations