Browsing by Author "Horisaki, Ryoichi"

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    Compressive holography of diffuse objects.
    (Appl Opt, 2010-12-01) Choi, Kerkil; Horisaki, Ryoichi; Hahn, Joonku; Lim, Sehoon; Marks, Daniel L; Schulz, Timothy J; Brady, David J
    We propose an estimation-theoretic approach to the inference of an incoherent 3D scattering density from 2D scattered speckle field measurements. The object density is derived from the covariance of the speckle field. The inference is performed by a constrained optimization technique inspired by compressive sensing theory. Experimental results demonstrate and verify the performance of our estimates.
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    Generalized sampling using a compound-eye imaging system for multi-dimensional object acquisition.
    (Opt Express, 2010-08-30) Horisaki, Ryoichi; Choi, Kerkil; Hahn, Joonku; Tanida, Jun; Brady, David J
    In this paper, we propose generalized sampling approaches for measuring a multi-dimensional object using a compact compound-eye imaging system called thin observation module by bound optics (TOMBO). This paper shows the proposed system model, physical examples, and simulations to verify TOMBO imaging using generalized sampling. In the system, an object is modulated and multiplied by a weight distribution with physical coding, and the coded optical signal is integrated on to a detector array. A numerical estimation algorithm employing a sparsity constraint is used for object reconstruction.
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    Imaging through turbulence using compressive coherence sensing.
    (Opt Lett, 2010-03-15) Wagadarikar, Ashwin A; Marks, Daniel L; Choi, Kerkil; Horisaki, Ryoichi; Brady, David J
    Previous studies have shown that the isoplanatic distortion due to turbulence and the image of a remote object may be jointly estimated from the 4D mutual intensity across an aperture. This Letter shows that decompressive inference on a 2D slice of the 4D mutual intensity, as measured by a rotational shear interferometer, is sufficient for estimation of sparse objects imaged through turbulence. The 2D slice is processed using an iterative algorithm that alternates between estimating the sparse objects and estimating the turbulence-induced phase screen. This approach may enable new systems that infer object properties through turbulence without exhaustive sampling of coherence functions.
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    Inline holographic coherent anti-Stokes Raman microscopy.
    (Opt Express, 2010-04-12) Xu, Qian; Shi, Kebin; Li, Haifeng; Choi, Kerkil; Horisaki, Ryoichi; Brady, David; Psaltis, Demetri; Liu, Zhiwen
    We demonstrate a simple approach for inline holographic coherent anti-Stokes Raman scattering (CARS) microscopy, in which a layer of uniform nonlinear medium is placed in front of a specimen to be imaged. The reference wave created by four-wave mixing in the nonlinear medium can interfere with the CARS signal generated in the specimen to result in an inline hologram. We experimentally and theoretically investigate the inline CARS holography and show that it has chemical selectivity and can allow for three-dimensional imaging.