Chapter

Emerging Trends in Visual Computing

Volume 5416 of the series Lecture Notes in Computer Science pp 238-253

Computational Photography: Epsilon to Coded Photography

  • Ramesh RaskarAffiliated withMedia Laboratory, Massachusetts Institute of Technology

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Abstract

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.

Keywords

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