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    Modeling classical wavefront sensors

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    Name:
    oe-28-4-5273.pdf
    Size:
    1.582Mb
    Format:
    PDF
    Description:
    Accepted manuscript
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    Type
    Article
    Authors
    Wang, Congli cc
    Fu, Qiang cc
    Dun, Xiong
    Heidrich, Wolfgang cc
    KAUST Department
    Computational Imaging Group
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering
    Electrical Engineering Program
    Visual Computing Center (VCC)
    Date
    2020-02-11
    Online Publication Date
    2020-02-11
    Print Publication Date
    2020-02-17
    Submitted Date
    2019-11-15
    Permanent link to this record
    http://hdl.handle.net/10754/661616
    
    Metadata
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    Abstract
    We present an image formation model for deterministic phase retrieval in propagation-based wavefront sensing, unifying analysis for classical wavefront sensors such as Shack-Hartmann (slopes tracking) and curvature sensors (based on Transport-of-Intensity Equation). We show how this model generalizes commonly seen formulas, including Transport-of-Intensity Equation, from small distances and beyond. Using this model, we analyze theoretically achievable lateral wavefront resolution in propagation-based deterministic wavefront sensing. Finally, via a prototype masked wavefront sensor, we show simultaneous bright field and phase imaging numerically recovered in real-time from a single-shot measurement.
    Citation
    Wang, C., Fu, Q., Dun, X., & Heidrich, W. (2020). Modeling classical wavefront sensors. Optics Express, 28(4), 5273. doi:10.1364/oe.381349
    Sponsors
    King Abdullah University of Science and Technology (Center Partnership Funding, Individual Baseline Funding). Portions of this work were presented at the Computational Optical Sensing and Imaging (COSI) Meeting in 2019, paper number CM1A.4.
    Publisher
    The Optical Society
    Journal
    Optics Express
    DOI
    10.1364/OE.381349
    Additional Links
    https://www.osapublishing.org/abstract.cfm?URI=oe-28-4-5273
    ae974a485f413a2113503eed53cd6c53
    10.1364/OE.381349
    Scopus Count
    Collections
    Articles; Computer Science Program; Electrical Engineering Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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