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    Focus detection from digital in-line holograms based on spectral l1 norms

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    OSA_prefocus_WHOAS.pdf (1.853Mb)
    Date
    2007-05-16
    Author
    Li, Weichang  Concept link
    Loomis, Nicholas C.  Concept link
    Hu, Qiao  Concept link
    Davis, Cabell S.  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/1928
    As published
    https://doi.org/10.1364/JOSAA.24.003054
    Abstract
    In this paper a rapid focus detection technique is developed for objects imaged using digital in-line holograms. It differs from previous approaches in that it is based directly on the spectral content of the object images and does not need a full reconstruction of the actual images. It is based on new focus metrics defined as the l1 norms of the object spectral components associated with the real and imaginary parts of the reconstruction kernel. Furthermore, these l1 norms can be computed efficiently in the frequency domain using a polar coordinate system, yielding a drastic speedup of about two orders of magnitude compared with image-based focus detection. The subsequent reconstruction, when done selectively over these detected focus distances, leads to significant computational savings. Focus detection results from holograms of plankton are demonstrated showing that the technique is both accurate and robust.
    Description
    Author Posting. © Optical Society of America, 2007. This is the author's version of the work. It is posted here by permission of Optical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Optical Society of America A, 24 (2007): 3054-3062, doi:10.1364/JOSAA.24.003054.
    Collections
    • Applied Ocean Physics and Engineering (AOP&E)
    • Biology
    Suggested Citation
    Preprint: Li, Weichang, Loomis, Nicholas C., Hu, Qiao, Davis, Cabell S., "Focus detection from digital in-line holograms based on spectral l1 norms", 2007-05-16, https://doi.org/10.1364/JOSAA.24.003054, https://hdl.handle.net/1912/1928
     
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