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23 April 2019 Improving speed and accuracy of phase retrieval applying two in-line hologram recordings
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Abstract
In the case of in-line digital holographic microscopes the retrieval of the phase information is indispensable to remove the twin image noise and to characterize the thickness and refractive index distribution of the measured objects. The existing phase reconstructing algorithms, especially, when the goal is to reach high resolution, suffer from really slow convergence. This can prevent their practical applicability. We introduce here a simple method that ensures accurate, high resolution and fast phase retrieval from two holograms recorded in different distances. The so far frequently applied phase retrieval algorithms converge with tolerable speed if the Fresnel number of the system is small enough. This is the consequence that in this case the diffraction of the twin image spreads substantially over the applied object support and thus the support constraint can provide sufficient amount of data for the efficient phase retrieval. However, if the recording measurement Fresnel number is small, the finite aperture of the hologram limits the proper recording of the high spatial frequencies of the object diffraction. In this case the convergence of the phase retrieval will be really fast, but inaccurate. Therefore, we propose to record two different holograms with small and large Fresnel numbers accordingly. From the first one we can reconstruct the low spatial frequencies of the object at a high rate. Subsequently, we can use this partial reconstruction to speed up the reconstruction of the so far not correctly recalled high spatial frequencies, by applying the second hologram.
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
László R. Orzó, Márton Zs. Kiss, and Ákos Zarándy "Improving speed and accuracy of phase retrieval applying two in-line hologram recordings", Proc. SPIE 11030, Holography: Advances and Modern Trends VI, 110300Y (23 April 2019); https://doi.org/10.1117/12.2520431
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