Unsupervised speckle denoising in digital holographic interferometry based on 4-f optical simulation integrated cycle-consistent generative adversarial network.

The speckle noise generated during digital holographic interferometry (DHI) is unavoidable and difficult to eliminate, thus reducing its accuracy. We propose a self-supervised deep-learning speckle denoising method using a cycle-consistent generative adversarial network to mitigate the effect of speckle noise. The proposed method integrates a 4-f optical speckle noise simulation module with a parameter generator. In addition, it uses an unpaired dataset for training to overcome the difficulty in obtaining noise-free images and paired data from experiments. The proposed method was tested on both simulated and experimental data, with results showing a 6.9% performance improvement compared with a conventional method and a 2.6% performance improvement compared with unsupervised deep learning in terms of the peak signal-to-noise ratio. Thus, the proposed method exhibits superior denoising performance and potential for DHI, being particularly suitable for processing large datasets.

Refocus criterion from image-plane speckle correlation in digital holographic interferometry.

In digital holography and holographic interferometry, refocusing to the correct image plane can be challenging and may be obtained by various metrics. This paper proposes a digital refocus approach utilizing the linear relationship between in-plane speckle motion and defocus as a response to an induced phase gradient. The theory based on cross-correlations between pairs of intensity images reconstructed at different distances from the recording plane is discussed. Two simple metrics, based on the cross-correlation properties of the reconstructed speckle images, are proposed and evaluated utilizing both simulations and experiments. Experiments exhibit similar trends in which the estimate of the correct reconstruction distance differs by a small amount between the two metrics. The difference is found less than 1% in the estimate of the true reconstruction distance. The results show that either metric is able to yield a sufficient reconstruction distance for the reconstruction of the image plane.

Decorrelation and anti-correlation from defocus in digital holographic interferometry.

This paper presents a theoretical modeling of the speckle noise decorrelation in digital Fresnel holographic interferometry in out-of-focus reconstructed images. The complex coherence factor is derived by taking into account the focus mismatch, which depends on both the sensor-to-object distance and the reconstruction distance. The theory is confirmed by both simulated data and experimental results. The very good agreement between data demonstrates the high relevance of the proposed modeling. The particular phenomenon of anti-correlation in phase data from holographic interferometry is highlighted and discussed.

Comparison of three full-field optical measurement techniques applied to vibration analysis.

Digital image correlation, deflectometry and digital holography are some of the full-field optical measurement techniques that have matured in recent years. Their use in vibroacoustic applications is gaining attention and there is a need for cataloging their performance in order to provide, to a broad community of users and potential future users, quantitative and qualitative evaluations of these three approaches. This paper presents an experimental comparison of the three optical methods in the context of vibration measurements, along with classical reference measurements provided by an accelerometer and a laser Doppler vibrometer. The study is carried out on two mechanical structures exhibiting various vibration responses when submitted to an impact.

Speckle denoising based on deep learning via a conditional generative adversarial network in digital holographic interferometry.

Speckle denoising can improve digital holographic interferometry phase measurements but may affect experimental accuracy. A deep-learning-based speckle denoising algorithm is developed using a conditional generative adversarial network. Two subnetworks, namely discriminator and generator networks, which refer to the U-Net and DenseNet layer structures are used to supervise network learning quality and denoising. Datasets obtained from speckle simulations are shown to provide improved noise feature extraction. The loss function is designed by considering the peak signal-to-noise ratio parameters to improve efficiency and accuracy. The proposed method thus shows better performance than other denoising algorithms for processing experimental strain data from digital holography.

Deep Learning Network for Speckle De-Noising in Severe Conditions.

Digital holography is well adapted to measure any modifications related to any objects. The method refers to digital holographic interferometry where the phase change between two states of the object is of interest. However, the phase images are corrupted by the speckle decorrelation noise. In this paper, we address the question of de-noising in holographic interferometry when phase data are polluted with speckle noise. We present a new database of phase fringe images for the evaluation of de-noising algorithms in digital holography. In this database, the simulated phase maps present characteristics such as the size of the speckle grains and the noise level of the fringes, which can be controlled by the generation process. Deep neural network architectures are trained with sets of phase maps having differentiated parameters according to the features. The performances of the new models are evaluated with a set of test fringe patterns whose characteristics are representative of severe conditions in terms of input SNR and speckle grain size. For this, four metrics are considered, which are the PSNR, the phase error, the perceived quality index and the peak-to-valley ratio. Results demonstrate that the models trained with phase maps with a diversity of noise characteristics lead to improving their efficiency, their robustness and their generality on phase maps with severe noise.

Deep learning speckle de-noising algorithms for coherent metrology: a review and a phase-shifted iterative scheme [Invited].

We present a review of deep learning algorithms dedicated to the processing of speckle noise in coherent imaging. We focus on methods that specifically process de-noising of input images. Four main classes of applications are described in this review: optical coherence tomography, synthetic aperture radar imaging, digital holography amplitude imaging, and fringe pattern analysis. We then present deep learning approaches recently developed in our group that rely on the retraining of residual convolutional neural network structures to process decorrelation phase noise. The paper ends with the presentation of a new approach that uses an iterative scheme controlled by an input SNR estimator associated with a phase-shifting procedure.

Roadmap on digital holography [Invited].

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

Modeling of speckle decorrelation in digital Fresnel holographic interferometry.

This paper presents analytical modeling of the speckle decorrelation noise in digital Fresnel holographic interferometry. The theoretical analysis is carried out by considering the complex coherence factor between two speckled images from two digitally reconstructed holograms at two different instants. The expression giving the modulus of the coherence factor is established and depends on the local surface deformation and parameters from the holographic setup. The analysis is supported by realistic simulations and experiments. Both simulations and experimental results exhibit a very good agreement with the theoretical prediction.

Theoretical analysis of surface-shape-induced decorrelation noise in multi-wavelength digital holography.

This paper presents analytical modelling for describing the speckle noise decorrelation in phase data from two- or multiple-wavelength digital holography. A novel expression for the modulus of the coherence factor is proposed for the case of two-wavelength speckle decorrelation from imaging roughness and surface shape through an optical system. The expression permits us to estimate the speckle decorrelation phase noise in surface shape measurements. The theoretical analysis is supported by realistic simulations including both the surface roughness and shape. The results demonstrate the very good agreement between the modulus of the coherence factor estimated with the simulation and the one calculated with theory.

Influence of noise-reduction techniques in sparse-data sample rotation tomographic imaging.

Data acquisition and processing is a critical issue for high-speed applications, especially in three-dimensional live cell imaging and analysis. This paper focuses on sparse-data sample rotation tomographic reconstruction and analysis with several noise-reduction techniques. For the sample rotation experiments, a live Candida rugosa sample is used and controlled by holographic optical tweezers, and the transmitted complex wavefronts of the sample are recorded with digital holographic microscopy. Three different cases of sample rotation tomography were reconstructed for dense angle with a step rotation at every 2°, and for sparse angles with step rotation at every 5° and 10°. The three cases of tomographic reconstruction performance are analyzed with consideration for data processing using four noise-reduction techniques. The experimental results demonstrate potential capability in retaining the tomographic image quality, even at the sparse angle reconstructions, with the help of noise-reduction techniques.

Noise and bias in off-axis digital holography for measurements in acoustic waveguides.

This paper discusses noise and bias in the method of holographic interferometry applied to the study of acoustics phenomena. The influence of noise on the measurement of acoustic pressure is described by an analytical approach. Relationships to quantify the minimum measurable fluid density and acoustic pressure are given by taking into account the experimental parameters of the setup. These parameters are related to the spatial bandwidths, number of electrons in pixels, readout noise, and quantization noise. Experimental results show that theoretical relations are relatively close to experimental data and that the lower pressure measurement limit is on the order of 15 Pa for the acoustics pressure. The case of waveguides excited by an internal or external acoustic source is investigated. Specifically, for the case of studies in thermoacoustics, this paper demonstrates that the parasitic coupling of vibrations can be compensated. The proposed method is based on the determination of the amplitude and phase of the parasitic oscillation, requiring a few assumptions related to the physics of the underlying phenomenon. Successful compensation is obtained and yields experimental data in agreement with the theoretical predictions.

Lock-in vibration retrieval based on high-speed full-field coherent imaging.

The use of high-speed cameras permits to visualize, analyze or study physical phenomena at both their time and spatial scales. Mixing high-speed imaging with coherent imaging allows recording and retrieving the optical path difference and this opens the way for investigating a broad variety of scientific challenges in biology, medicine, material science, physics and mechanics. At high frame rate, simultaneously obtaining suitable performance and level of accuracy is not straightforward. In the field of mechanics, this prevents high-speed imaging to be applied to full-field vibrometry. In this paper, we demonstrate a coherent imaging approach that can yield full-field structural vibration measurements with state-of-the-art performances in case of high spatial and temporal density measurements points of holographic measurement. The method is based on high-speed on-line digital holography and recording a short time sequence. Validation of the proposed approach is carried out by comparison with a scanning laser Doppler vibrometer and by realistic simulations. Several error criteria demonstrate measurement capability of yielding amplitude and phase of structural deformations.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 20-23 May 2019 in Bordeaux, France. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes 46 papers in AO and 9 in JOSA A and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH Conference (DH 2020) will be held from 22 to 26 June in Vancouver, Canada, as part of the OSA Imaging and Applied Optics Congress.

Optimal processing scheme for restoration of phase data corrupted by strong decorrelation noise and dislocations.

The presence of speckle noise and dislocations makes phase restoration potentially difficult in quantitative phase imaging and metrology. Unfortunately, there is no appropriate approach to deal with phase data corrupted by high speckle noise and phase dislocations. Usually, processing schemes may deal with low-pass phase filtering, phase unwrapping, or phase inpainting. This paper discusses the efficient processing to deal with noisy phase maps corrupted with phase dislocations. Six processing schemes, combining four operations, are evaluated. The investigation is carried out by realistic numerical simulations in which strong decorrelation phase noise and phase dislocations are generated. As a result, most robust and faster processing is established. The applicability of the optimal scheme is demonstrated through deformation measurement in dental materials.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held 20-23 May 2019 in Bordeaux, France. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes 46 papers in AO and 9 in JOSA A and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH Conference (DH 2020) will be held from 22 to 26 June in Vancouver, Canada, as part of the OSA Imaging and Applied Optics Congress.

Contrast transfer function of de-noising algorithms.

This paper presents a comprehensive study on the contrast transfer function of de-noising algorithms. In order to cover a broad variety of methods, 45 de-noising algorithms are chosen considering their recognized efficiency in the different application domains of image processing. Advanced methods are targeted: wavelet transform-based algorithms with Daubechies, symlets, curvelets, contourlets, patch-based methods such as BM3D, NL-means algorithms and deep learning approaches; in addition, classical spatial filtering methods are considered, such as Wiener, median, Gauss filtering, and adaptive filtering approaches such as anisotropic diffusion and synthetic aperture radar filtering. The contrast transfer function is provided for each algorithm. Ranking of the set of de-noising algorithms is established according to proposed metrics. The paper provides practical methodology and novel results dedicated to the evaluation of the contrast transfer function of de-noising approaches from literature.

Digital holography and 3D imaging: introduction to the Applied Optics and Journal of the Optical Society of America A joint feature issue.

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held June 25-June 28, 2018, in Orlando, Florida, USA. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes thirty-eight papers in AO and nine in JOSA A, and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH Conference (DH 2019) will be held May 19-May 23 in Bordeaux, France.

Comparative study of multi-look processing for phase map de-noising in digital Fresnel holographic interferometry.

This paper presents a comparative study of multi-look approaches for de-noising phase maps from digital holographic interferometry. A database of 160 simulated phase fringe patterns with eight different phase fringe patterns with fringe diversity was computed. For each fringe pattern, 20 realistic noise realizations are generated in order to simulate a multi-look process with 20 inputs. A set of 22 de-noising algorithms was selected and processed for each simulation. Three approaches for multi-look processing are evaluated. Quantitative appraisal is obtained using two metrics. The results show good agreement for algorithm rankings obtained with both metrics. One singular and highly practical result of the study is that a multi-look approach with average looks before noise processing performs better than averaging computed with all de-noised looks. The results also demonstrate that the two-dimensional windowed Fourier transform filtering exhibits the best performance in all cases and that the block-matching 3D (BM3D) algorithm is second in the ranking.

Digital holography and 3D imaging: introduction to the Applied Optics and Journal of the Optical Society of America A joint feature issue.

The OSA Topical Meeting on Digital Holography and 3D Imaging (DH) was held June 25-28, 2018, in Orlando, Florida, USA. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year, AO and the Journal of the Optical Society of America A (JOSA A) jointly decided to have one such feature issue in each journal. This feature issue includes thirty-eight papers in AO and nine in JOSA A, and covers a large range of topics, reflecting the rapidly expanding techniques and applications of digital holography and 3D imaging. The upcoming DH Conference (DH 2019) will be held May 19-23 in Bordeaux, France.