Gigapixel computational imaging

Oliver S. Cossairt, Daniel Miau, Shree K. Nayar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Scopus citations

Abstract

Today, consumer cameras produce photographs with tens of millions of pixels. The recent trend in image sensor resolution seems to suggest that we will soon have cameras with billions of pixels. However, the resolution of any camera is fundamentally limited by geometric aberrations. We derive a scaling law that shows that, by using computations to correct for aberrations, we can create cameras with unprecedented resolution that have low lens complexity and compact form factor. In this paper, we present an architecture for gigapixel imaging that is compact and utilizes a simple optical design. The architecture consists of a ball lens shared by several small planar sensors, and a post-capture image processing stage. Several variants of this architecture are shown for capturing a contiguous hemispherical field of view as well as a complete spherical field of view. We demonstrate the effectiveness of our architecture by showing example images captured with two proof-of-concept gigapixel cameras.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Computational Photography, ICCP 2011
DOIs
StatePublished - May 23 2011
Event2011 IEEE International Conference on Computational Photography, ICCP 2011 - Pittsburgh, PA, United States
Duration: Apr 8 2011Apr 10 2011

Publication series

Name2011 IEEE International Conference on Computational Photography, ICCP 2011

Other

Other2011 IEEE International Conference on Computational Photography, ICCP 2011
CountryUnited States
CityPittsburgh, PA
Period4/8/114/10/11

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Fingerprint Dive into the research topics of 'Gigapixel computational imaging'. Together they form a unique fingerprint.

Cite this