Compressive sensing for improved depth discrimination in 3D holographic reconstruction

Yair Rivenson, Adrian Stern, Bahram Javidi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Compressive holography has attracted significant interest since its introduction three about years ago. In this paper, we present an overview of our work on the ability to reconstruct a 3D volume from its 2D recorded compressive hologram. Using the single-exposure on-line (SEOL) setup, we show how CS applied to this naturally underdetermined problem enables the improved sectioning (or depth discrimination) of the reconstructed volume, when compared with standard in-line holography. We also present the mathematical guarantees for the reconstruction of the 3D volume features from its single 2D hologram and their physical implications for sectioning of 3D volume.

Original languageEnglish
Title of host publicationThree-Dimensional Imaging, Visualization, and Display 2013
StatePublished - 12 Aug 2013
EventThree-Dimensional Imaging, Visualization, and Display 2013 - Baltimore, MD, United States
Duration: 29 Apr 201330 Apr 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


ConferenceThree-Dimensional Imaging, Visualization, and Display 2013
Country/TerritoryUnited States
CityBaltimore, MD


  • Compressed sensing
  • Compressive imaging
  • Compressive sensing
  • Computational imaging
  • Digital holography
  • Inverse problems

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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