Abstract

Reconstruction of phase objects is a central problem in digital holography, whose various applications include microscopy, biomedical imaging, and fluid mechanics. Starting from a single in-line hologram, there is no direct way to recover the phase of the diffracted wave in the hologram plane. The reconstruction of absorbing and phase objects therefore requires the inversion of the non-linear hologram formation model. We propose a regularized reconstruction method that includes several physically-grounded constraints such as bounds on transmittance values, maximum/minimum phase, spatial smoothness or the absence of any object in parts of the field of view. To solve the non-convex and non-smooth optimization problem induced by our modeling, a variable splitting strategy is applied and the closed-form solution of the sub-problem (the so-called proximal operator) is derived. The resulting algorithm is efficient and is shown to lead to quantitative phase estimation on reconstructions of accurate simulations of in-line holograms based on the Mie theory. As our approach is adaptable to several in-line digital holography configurations, we present and discuss the promising results of reconstructions from experimental in-line holograms obtained in two different applications: the tracking of an evaporating droplet (size ∼ 100μm) and the microscopic imaging of bacteria (size ∼ 1μm).

Highlights

  • The principle of in-line holography was first proposed by Dennis Gabor in 1948 [1]

  • The reconstruction procedure is tested in the field of fluid mechanics

  • In-line holograms of these droplets are recorded on the CMOS sensor of a Phantom V611 high speed camera at a framerate of 3 kHz

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Summary

Introduction

The principle of in-line holography was first proposed by Dennis Gabor in 1948 [1] It uses a coherent - or semi coherent - optical illumination to image absorbing and/or phase objects. To tackle the difficulty involved in minimization, we use a "variable splitting" strategy and derive the closed-form global solution of the sub-problem that contains all the non-linear constraints and non-smooth terms, and part of the non-convexity. This proximal operator is an important contribution of our work since it forms the core of the reconstruction method and reduces the number of additional parameters involved in the variable-splitting process [25]. We discuss the quality of the reconstructions based on experimental in-line holograms obtained in two different applications: fluid mechanics with the tracking of an evaporating droplet (size ∼ 100μm) and microscopy of bacteria (size ∼ 1μm)

Hologram formation model
Regularized inversion
Physical constraints on the transmittance of the objects
Proposed iterative reconstruction algorithm
Context and experiments
Simulations of evaporating droplets using the Mie theory
Reconstructions from the sequence of experimental holograms
Context and experimental bench
Conclusion & discussion
Full Text
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