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2 November 2018 Single assignment based nearest neighbor interpolation algorithm for digital holographic diffraction tomography
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Abstract
Digital holographic diffraction tomography combines digital holography with optical diffraction tomography. According to the Fourier diffraction theory, the spectrum information is unevenly distributed on a Ewald sphere, and most of these data cannot exactly locate on the 3D matrix points. To solve this problem, a single assignment based nearest neighbor interpolation method is proposed. Firstly, the points to be interpolated are chosen on the 3D matrix. For each angle, a search scope is confirmed by two spheres with a radius R (k0-0.5< R <k0+0.5), where k0 is the radius of Ewald sphere. Then, the point on the 3D matrix is assigned by the value of the nearest neighbor point within this scope. After the assignment of the frequency information for all the angles, the object function is obtained by 3D inverse Fourier transform. In order to verify the feasibility of this method, a digital holographic diffraction tomography system is built. The 3D refractive index (RI) distribution of a microsphere with known RI 1.4607 is measured. Comparing with the conventional nearest neighbor interpolation algorithm, the relative error is reduced from 0.51% to 0.36%. It is demonstrated that the proposed algorithm can improve the reconstruction accuracy for diffraction tomography.
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Yuanyuan Yuan, Yunxin Wang, Jie Zhao, Dayong Wang, Weining Chi, and Lu Rong "Single assignment based nearest neighbor interpolation algorithm for digital holographic diffraction tomography", Proc. SPIE 10818, Holography, Diffractive Optics, and Applications VIII, 108181K (2 November 2018); https://doi.org/10.1117/12.2500360
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