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

    Abstract

    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
    DOIs
    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
    Volume8738
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Conference

    ConferenceThree-Dimensional Imaging, Visualization, and Display 2013
    Country/TerritoryUnited States
    CityBaltimore, MD
    Period29/04/1330/04/13

    Keywords

    • 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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