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Strategies for reducing speckle noise in digital holography

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TLDR
A broad discussion about the noise issue in DH is provided, with the aim of covering the best-performing noise reduction approaches that have been proposed so far and quantitative comparisons among these approaches will be presented.
Abstract
Digital holography (DH) has emerged as one of the most effective coherent imaging technologies. The technological developments of digital sensors and optical elements have made DH the primary approach in several research fields, from quantitative phase imaging to optical metrology and 3D display technologies, to name a few. Like many other digital imaging techniques, DH must cope with the issue of speckle artifacts, due to the coherent nature of the required light sources. Despite the complexity of the recently proposed de-speckling methods, many have not yet attained the required level of effectiveness. That is, a universal denoising strategy for completely suppressing holographic noise has not yet been established. Thus the removal of speckle noise from holographic images represents a bottleneck for the entire optics and photonics scientific community. This review article provides a broad discussion about the noise issue in DH, with the aim of covering the best-performing noise reduction approaches that have been proposed so far. Quantitative comparisons among these approaches will be presented.

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Three-Dimensional Imaging and ProcessingUsing Computational Holographic Imaging

TL;DR: Digital holography is a technique that permits digital capture of holograms and subsequent processing on a digital computer as mentioned in this paper, and various applications of this technique cover three-dimensional (3-D) imaging as well as several problems.
Journal ArticleDOI

Deep learning in holography and coherent imaging.

TL;DR: In a discussion of the topic, Yair Rivenson, Yichen Wu, and Aydogan Ozcan explain how once “trained” with appropriate datasets, neural networks can learn to reconstruct images with added benefits such as improved phase recovery and extended depth of field as well as enhanced spatial resolution and superior signal-to-noise ratio.
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Deep learning in optical metrology: a review

TL;DR: Deep learning-enabled optical metrology is a kind of data-driven approach, which has already provided numerous alternative solutions to many challenging problems in this field with better performances as discussed by the authors .
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Deep learning in optical metrology: a review

TL;DR: Deep learning-enabled optical metrology is a kind of data-driven approach, which has already provided numerous alternative solutions to many challenging problems in this field with better performances as discussed by the authors .
Posted Content

Imaging blood cells through scattering biological tissue using speckle scanning microscopy

TL;DR: Clear images of multiple cells were obtained with subcellular resolution and good image fidelity, provided that the object dimension was smaller than the maximum scanning range of the speckle pattern.
References
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Journal ArticleDOI

Effects of quantization in phase-shifting digital holography

TL;DR: The influence of bit-depth limitation in quantization has been demonstrated in a numerical simulation for spot-array patterns with linearly varying intensities and a continuous intensity object and the quality of the reconstructed images has been evaluated for the different quantization levels.
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Quantitative appraisal for noise reduction in digital holographic phase imaging

TL;DR: There exists an anti-correlation between the phase error and the quality index which indicates that the phase errors are mainly structural distortions in the fringe pattern and the signal-to-noise ratio gain has been observed.
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Image quality improvement of digital holography by superposition of reconstructed images obtained by multiple wavelengths.

TL;DR: A method to improve the image quality of a digital holographic reconstructed image by means of speckle reduction by superposing reconstructed images with different wavelengths.
Journal ArticleDOI

Spatial coherence of random laser emission.

TL;DR: This work demonstrates that random lasers can be controlled to provide intense, spatially incoherent emission for applications in which spatial cross talk or speckle limit performance.
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Full-field and single-shot quantitative phase microscopy using dynamic speckle illumination

TL;DR: An off-axis quantitative phase microscopy that works for a light source with an extremely short spatial coherence length in order to reduce the diffraction noise and enhance the spatial resolution and depth selectivity is developed.
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