Distributed feature-specific imaging

Jun Ke, Premchandra Shankar, Mark A Neifeld

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

Abstract

We describe a distributed network of low-power feature-specific (i.e., compressive) imagers. Several candidate projection types are compared. Linear minimum mean squared error estimation is used for reconstruction. Image quality and sensor lifetime are quantified.

Original languageEnglish (US)
Title of host publicationOptics InfoBase Conference Papers
PublisherOptical Society of America
ISBN (Print)1557528381, 9781557528384
StatePublished - 2007
EventComputational Optical Sensing and Imaging, COSI 2007 - Vancouver, Canada
Duration: Jun 18 2007Jun 18 2007

Other

OtherComputational Optical Sensing and Imaging, COSI 2007
CountryCanada
CityVancouver
Period6/18/076/18/07

Fingerprint

Image sensors
projection
Imaging techniques
life (durability)
sensors
Error analysis
Image quality

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

Cite this

Ke, J., Shankar, P., & Neifeld, M. A. (2007). Distributed feature-specific imaging. In Optics InfoBase Conference Papers Optical Society of America.

Distributed feature-specific imaging. / Ke, Jun; Shankar, Premchandra; Neifeld, Mark A.

Optics InfoBase Conference Papers. Optical Society of America, 2007.

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

Ke, J, Shankar, P & Neifeld, MA 2007, Distributed feature-specific imaging. in Optics InfoBase Conference Papers. Optical Society of America, Computational Optical Sensing and Imaging, COSI 2007, Vancouver, Canada, 6/18/07.
Ke J, Shankar P, Neifeld MA. Distributed feature-specific imaging. In Optics InfoBase Conference Papers. Optical Society of America. 2007
Ke, Jun ; Shankar, Premchandra ; Neifeld, Mark A. / Distributed feature-specific imaging. Optics InfoBase Conference Papers. Optical Society of America, 2007.
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