Thin digital imaging systems using focal plane coding

Andrew D. Portnoy, Nikos P. Pitsianis, David J. Brady, Jungpeng Guo, Michael A. Fiddy, Michael R. Feldman, Robert D. Te Kolste

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

13 Scopus citations


With this work we show the use of focal plane coding to produce nondegenerate data between subapertures of an imaging system. Subaperture data is integrated to form a single high resolution image. Multiple apertures generate multiple copies of a scene on the detector plane. Placed in the image plane, the focal plane mask applies a unique code to each of these sub-images. Within each sub-image, each pixel is masked so that light from only certain optical pixels reaches the detector. Thus, each sub-image measures a different linear combination of optical pixels. Image reconstruction is achieved by inversion of the transformation performed by the imaging system. Registered detector pixels in each sub-image represent the magnitude of the projection of the same optical information onto different sampling vectors. Without a coding element, the imaging system would be limited by the spatial frequency response of the electronic detector pixel. The small mask features allow the imager to broaden this response and reconstruct higher spatial frequencies than a conventional coarsely sampling focal plane.

Original languageEnglish (US)
Title of host publicationComputational Imaging IV - Proceedings of SPIE-IS and T Electronic Imaging
StatePublished - 2006
Externally publishedYes
EventComputational Imaging IV - San Jose, CA, United States
Duration: Jan 16 2006Jan 18 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceComputational Imaging IV
Country/TerritoryUnited States
CitySan Jose, CA


  • Computational imaging
  • Focal plane coding
  • Multi-aperture imaging
  • Super-resolution

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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