Computational Photography: Epsilon to Coded Imaging
published: Dec. 5, 2008, recorded: November 2008, views: 13224
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
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.
Download slides: etvc08_raskar_cpetci_01.ppt (39.0 MB)
Download article: etvc08_raskar_cpetci_article_01.pdf (11.1 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !