Compressive stereo cameras for computing disparity maps

Vicha Treeaporn, Amit Ashok, Mark A. Neifeld

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


Compressive imaging employs the direct measurement of object features and has been shown to offer both performance (e.g., improved reconstructed image fidelity) and cost (e.g., reduced number of measurements relative to the native dimensionality) advantages. We examine compressive imaging within a stereo vision application in which a traditional correspondence algorithm is used to find pixel disparity maps. Through simulation we show that compressive imaging provides sufficient image fidelity with 12.8× compression to compute disparity maps with less that 4.5% error on average at 0.5% relative measurement noise strength.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2013
PublisherOptical Society of America (OSA)
ISBN (Print)9781557529756
StatePublished - 2013
EventComputational Optical Sensing and Imaging, COSI 2013 - Arlington, VA, United States
Duration: Jun 23 2013Jun 27 2013

Publication series

NameOptics InfoBase Conference Papers
ISSN (Electronic)2162-2701


OtherComputational Optical Sensing and Imaging, COSI 2013
Country/TerritoryUnited States
CityArlington, VA

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics


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