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    Computational imaging using lightweight diffractive-refractive optics

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    ComputationalImagingUsingLightweightDiffractiveRefractiveOptics.pdf
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    2.338Mb
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    Description:
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    Type
    Article
    Authors
    Peng, Yifan
    Fu, Qiang cc
    Amata, Hadi cc
    Su, Shuochen
    Heide, Felix
    Heidrich, Wolfgang cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Visual Computing Center (VCC)
    Date
    2015-11-23
    Online Publication Date
    2015-11-23
    Print Publication Date
    2015-11-30
    Permanent link to this record
    http://hdl.handle.net/10754/583044
    
    Metadata
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    Abstract
    Diffractive optical elements (DOE) show great promise for imaging optics that are thinner and more lightweight than conventional refractive lenses while preserving their light efficiency. Unfortunately, severe spectral dispersion currently limits the use of DOEs in consumer-level lens design. In this article, we jointly design lightweight diffractive-refractive optics and post-processing algorithms to enable imaging under white light illumination. Using the Fresnel lens as a general platform, we show three phase-plate designs, including a super-thin stacked plate design, a diffractive-refractive-hybrid lens, and a phase coded-aperture lens. Combined with cross-channel deconvolution algorithm, both spherical and chromatic aberrations are corrected. Experimental results indicate that using our computational imaging approach, diffractive-refractive optics is an alternative candidate to build light efficient and thin optics for white light imaging.
    Citation
    Computational imaging using lightweight diffractive-refractive optics 2015, 23 (24):31393 Optics Express
    Publisher
    The Optical Society
    Journal
    Optics Express
    DOI
    10.1364/OE.23.031393
    Additional Links
    https://www.osapublishing.org/abstract.cfm?URI=oe-23-24-31393
    ae974a485f413a2113503eed53cd6c53
    10.1364/OE.23.031393
    Scopus Count
    Collections
    Articles; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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