Coding and signal inference in compressive holography

Kerkil Choi, Ryoichi Horisaki, Daniel L. Marks, David J. Brady

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

Abstract

Compressive sensing enables highly accurate signal reconstruction from fewer measurements than the number of samples in a signal to be estimated. This paper describes a theoretical framework for 3D tomographic reconstruction from 2D holographic measurements.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2009
PublisherOptical Society of America (OSA)
ISBN (Print)9781557528780
DOIs
StatePublished - 2009
Externally publishedYes
EventComputational Optical Sensing and Imaging, COSI 2009 - San Jose, CA, United States
Duration: Oct 13 2009Oct 15 2009

Publication series

NameOptics InfoBase Conference Papers
ISSN (Electronic)2162-2701

Conference

ConferenceComputational Optical Sensing and Imaging, COSI 2009
Country/TerritoryUnited States
CitySan Jose, CA
Period10/13/0910/15/09

ASJC Scopus subject areas

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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