Less Is More: Coded Computational Photography

  • Ramesh Raskar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4843)


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 involve taking multiple sequential photos by changing scene parameters and fusing the photos to create a richer representation. 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.


High Dynamic Range Microlens Array High Dynamic Range Image Digital Sensor Optical Heterodyne 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ramesh Raskar
    • 1
  1. 1.Mitsubishi Electric Research Labs (MERL), Cambridge, MAUSA

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