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.
Less Is More: Coded Computational Photography
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
High Dynamic Range , Microlens Array , High Dynamic Range Image , Digital Sensor , Optical Heterodyne Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence , Biometrics , Algorithm Analysis and Problem Complexity
Mobile Computational Photography
British Library Online Contents | 2013
|Matt Prior - Less is more, more or less
Online Contents | 2013
Kraftfahrwesen | 2008
|On the Mathematical Foundations of Computational Photography
British Library Online Contents | 2016
|British Library Online Contents | 1999