Paper
11 November 2014 Iterative digital in-line holographic reconstruction with improved resolution by data interpolation
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Abstract
Digital in-line holography (DIH) is a lensless imaging technique that can be used to build low-cost and compact imaging systems. In DIH, the in-line hologram is recorded by a CMOS or CCD sensor and later used to reconstruct the image of the sample. The imaging resolution is determined by the system numerical aperture provided that the pixel size is smaller than the required Nyquist criteria for sampling distance. In the case of short sample-to-sensor distance, pixel size is often a limiting factor for the resolution. To solve this problem, we propose to use iterative method along with data interpolation for the holographic reconstruction. Proof-of-concept numerical simulations have been done to show the effectiveness of our method. In our algorithm, the optical field is propagated back and forth between the sample plane and the sensor plane while using the measured intensity and a priori information about the sample as constraints, following Gerchberg-Saxton and Fienup’s methods. The iteration will converge and we can get both intensity and phase information of the sample. Before the iteration, the intensity data matrix measured by the sensor is interpolated to enlarge the matrix dimension and thus effectively reduce the pixel size. During the iteration, we apply the sensor plane constraints on only the measured intensity location but not the interpolated data location. In our simulation, we observed that during the iteration, the interpolated data will be changed reasonably and we can finally reconstruct the sample image with better resolution.
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Mingjun Wang and Jigang Wu "Iterative digital in-line holographic reconstruction with improved resolution by data interpolation", Proc. SPIE 9271, Holography, Diffractive Optics, and Applications VI, 927110 (11 November 2014); https://doi.org/10.1117/12.2071694
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KEYWORDS
3D image reconstruction

Holograms

Holography

Digital holography

Sensors

Image resolution

Image restoration

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