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Open AccessJournal ArticleDOI

Strategies for reducing speckle noise in digital holography

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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Citations
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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.
Journal ArticleDOI

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 .
Journal ArticleDOI

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

Low-loss high-speed speckle reduction using a colloidal dispersion

TL;DR: In this article, a simple and robust approach to reduce laser speckle is presented, which has limited the adoption of lasers in imaging and display applications, using colloidal solutions that can quickly reduce speckble contrast due to the Brownian motion of the scattering particles.
Journal ArticleDOI

Coherent noise reduction in digital holographic microscopy by laterally shifting camera

TL;DR: In this article, a method to reduce the inherited coherent noise degrades the imaging quality and resolution in digital holographic microscopy is proposed, where a series of digital holograms are recorded by laterally shifting camera and reconstructed individually, and the additional lateral displacement and phase shift of reconstructed images due to the change of camera position are corrected by using the phase compensation and image registration algorithms.
Journal ArticleDOI

Denoising in digital speckle pattern interferometry using wave atoms

TL;DR: An effective method for speckle noise removal in digital Speckle pattern interferometry is presented, which is based on a wave-atom thresholding technique that improves the sparse representation of fringe patterns when compared with traditional expansions.
Journal ArticleDOI

Speckle correlation fringes denoising using stationary wavelet transform. Application in the wavelet phase evaluation technique

TL;DR: This method was used to denoise a simulated speckle fringe patterns, a good fidelity value was obtained and it has provided a phase distribution with a good accuracy.
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