Refocusing Photographs After Taking the Image

December 7, 2006 | Mark Goldstein | Digital | Comment | |

Refocus Imaging, Inc. Press Release

Every photographer is familiar with the frustration of losing a shot because the camera focused too slowly, or focused on the wrong thing. Recent camera technology innovations at Stanford University provide a new solution to this old problem. The idea is to capture extra information at the sensor, which is missing in conventional cameras. Special processing enables physical functions of the lens to be implemented in software. This approach provides unprecedented photographic features, such as the ability to refocus photographs after the image is taken. The underlying technology also enables dramatic improvements in lighting and sensitivity. For the novice, this means a more reliable camera that makes it easier to take great-looking pictures. For aficionados and professionals, this technology means unprecedented control over the quality of each image pixel.

At the December 13th COBA meeting (http://coba.tow.com), Ren Ng will be discussing his software and prototype camera that allows for refocusing after the fact. In this talk, Ren will present photographs taken with a prototype camera, discuss how it works and how he believes it will affect photographic science and art.

His research has been featured in the press, including Wired, Popular Science, Digital Photography Review, KNTV-NBC11 TechNow, KTVU-TV Fox 5 News, Photonics Spectra, MIT Tech Review, Stanford Review, slashdot, engadget, and more.

Speaker Bio
Ren Ng recently graduated with his PhD from the Computer Science department at Stanford University, and founded Refocus Imaging to commercialize his research. His PhD dissertation won the Arthur Samuel Thesis Award for the best dissertation in Computer Science at Stanford, and was nominated for the Association of Computing Machinery’s (ACM) Dissertation Award. Ren’s interests are in digital imaging systems, computer graphics, optics and applied mathematics. He holds an MS in Computer Science and BS in Mathematical and Computational Science from Stanford University.

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