Holographic Speckle Research Articles

Defect Isolation from Whole to Local Field Separation in Complex Interferometry Fringe Patterns through Development of Weighted Least-Squares Algorithm

In this paper, based on Gaussian 1σ-criterion and histogram segmentation, a weighted least-squares algorithm is applied and validated on digital holographic speckle pattern interferometric data to perform phase separation on the complex interference fields. The direct structural diagnosis tool is used to investigate defects and their impact on a complex antique wall painting of Giotto. The interferometry data is acquired with a portable off-axis interferometer set-up with a phase-shifted reference beam coupled with the object beam in front of the digital photosensitive medium. A digital holographic speckle pattern interferometry (DHSPI) system is used to register digital recordings of interferogram sequences over time. The surface is monitored for as long as it deforms prior to returning to its initial reference equilibrium state prior to excitation. The attempt to separate the whole vs. local defect complex amplitudes from the interferometric data is presented. The main aim is to achieve isolation and visualization of each defect’s impact amplitude in order to obtain detailed documentation of each defect and its structural impact on the surface for structural diagnosis purposes.

Architectural assessment of wall paintings using a multimodal and multi-resolution diagnostic approach: The test site of the Brancacci chapel in Firenze

Based on the analysis of the renaissance wall paintings by Masaccio, Masolino, and Filippino Lippi in the Brancacci chapel in Firenze, this paper discusses the use of complementary non-destructive techniques based on microwave and optical methods for the characterization of the structural integrity of the wall paintings and their support in masonry. The selected non-destructive techniques are the InfraRed Thermography (IRT), Ground Penetrating Radar (GPR), Microwave Reflectometry (MWR), and Digital Holographic Speckle Pattern Interferometry (DHSPI). In particular, the paper analyses the in-situ applicability of these techniques for the identification of the sequence of past interventions during centuries (stratigraphy analysis) and decay phenomena and defects, such as out-of-plumb or swelling area/elements, detachments, cracks and voids inside the wall. The results are compared with data obtained by means of consolidated techniques and methods, such as the Photogrammetry (performed by Structure from Motion method) and knocking test. The last one is normally used by restorers and conservators to recognize the presence of detachments. The proposed diagnostic strategy provides a survey from large scale by means of imaging techniques, to small scale increasing the spatial resolution thanks to the scanning of the surface by means of spot techniques. Therefore, the macroscopic survey of wall paintings was carried out using photogrammetry, in order to also provide metric information, to quantify the sizing out-of-plumb and swelling of the masonry or to locate of cracks, and followed by IRT. This preliminary morphometric survey was, supplemented by GPR, MWR and DHSPI for improve the results of the investigation. By combining these three techniques it was possible to inspect the entire thickness of the masonry (60­70 cm) with resolutions ranging from a few millimetres up to several centimetres. The combination of microwave-based and optical-based methods proved to be a valuable addition to routine methods for the holistic masonry diagnosis. Standard practice based on visual inspection and knocking test can be significantly improved and objectified by the proposed full-field, multi-sensor, multi-resolution approach.

Deep sound-field denoiser: optically-measured sound-field denoising using deep neural network.

This paper proposes a deep sound-field denoiser, a deep neural network (DNN) based denoising of optically measured sound-field images. Sound-field imaging using optical methods has gained considerable attention due to its ability to achieve high-spatial-resolution imaging of acoustic phenomena that conventional acoustic sensors cannot accomplish. However, the optically measured sound-field images are often heavily contaminated by noise because of the low sensitivity of optical interferometric measurements to airborne sound. Here, we propose a DNN-based sound-field denoising method. Time-varying sound-field image sequences are decomposed into harmonic complex-amplitude images by using a time-directional Fourier transform. The complex images are converted into two-channel images consisting of real and imaginary parts and denoised by a nonlinear-activation-free network. The network is trained on a sound-field dataset obtained from numerical acoustic simulations with randomized parameters. We compared the method with conventional ones, such as image filters, a spatiotemporal filter, and other DNN architectures, on numerical and experimental data. The experimental data were measured by parallel phase-shifting interferometry and holographic speckle interferometry. The proposed deep sound-field denoiser significantly outperformed the conventional methods on both the numerical and experimental data. Code is available on GitHub (https://github.com/nttcslab/deep-sound-field-denoiser).

Improving the Angular Visibility of Photopolymer-Based Reflection Holograms for Sensing Applications.

Volume reflection hologram-based sensors are designed to visibly change colour in response to a target stressor or analyte. However, reflection holograms fabricated in thick photopolymer films are highly angularly selective, making these sensors challenging to view and interpret by non-experts. Here, the use of speckle holography to improve the visibility of reflection holograms is presented. A novel recording approach combining speckle recording techniques with Denisyuk reflection recording geometry is described. The recorded speckle reflection grating operates as a series of multiplexed reflection gratings with a range of spatial frequencies, capable of reflecting light at a wider range of angles. A comparative study of the angular and wavelength selectivity of speckle and standard reflection gratings was conducted. The FWHM of the angular selectivity curves of the speckle reflection gratings is doubled (4°) in comparison to standard 4500 lines/mm reflection gratings (2°). The wavelength selectivity FWHM is also doubled from 4.2 to 8.6 nm. The comparative ability of the speckle and standard reflection gratings to act as colour-changing compressional pressure sensors in the 0.88-5.31 MPa range is described. Finally, we present a prototype reflection hologram viewer which enables the easy observation of angularly specific reflection holograms by non-experts.

Digital holographic speckle denoising method based on compound modulation of object light

为了克服在数字全息术中激光源高相干度造成的散斑噪声降低成像质量问题，论文提出将石英退偏器与电控液晶散射片相结合用于数字全息术中。通过在物光路中加入一个石英退偏器，利用退偏器的退偏性能使物光光路中的线偏光变成随机偏振光，降低与参考光的相干程度，实现对散斑噪声的抑制；通过给液晶散射片外加电场可以引起液晶分子的运动和光轴取向改变，调整液晶驱动电压大小来改变入射光的不同散射效果，有效地降低了光源的相干性；分别将单独采用石英退偏器和电控液晶散射片的重建图像与组合装置的重建图像进行对比分析，通过实验验证了所提方法的有效性。实验结果表明：两种实验对象在组合装置下的重建像峰值信噪比分别达到16.91和18.30，结构相似度为0.47和0.43，等效视数较原始重建像提高了42%和30%，散斑指数为1.52和1.29。论文提出的方法可较好地去除散斑噪声，保留更多的图像细节部分。

Smartphone-based holographic measurement of polydisperse suspended particulate matter with various mass concentration ratios

Real-time monitoring of suspended particulate matter (PM) has become essential in daily life due to the adverse effects of long-term exposure to PMs on human health and ecosystems. However, conventional techniques for measuring micro-scale particulates commonly require expensive instruments. In this study, a smartphone-based device is developed for real-time monitoring of suspended PMs by integrating a smartphone-based digital holographic microscopy (S-DHM) and deep learning algorithms. The proposed S-DHM-based PM monitoring device is composed of affordable commercial optical components and a smartphone. Overall procedures including digital image processing, deep learning training, and correction process are optimized to minimize the prediction error and computational cost. The proposed device can rapidly measure the mass concentrations of coarse and fine PMs from holographic speckle patterns of suspended polydisperse PMs in water with measurement errors of 22.8 ± 18.1% and 13.5 ± 9.8%, respectively. With further advances in data acquisition and deep learning training, this study would contribute to the development of hand-held devices for monitoring polydisperse non-spherical pollutants suspended in various media.

Surface Displacement Measurements of Artworks: New Data Processing for Speckle Pattern Interferometry

Curators have developed preventive conservation strategies and usually try to control the temperature (T) and relative humidity (RH) variations in the museum rooms to stabilise the artworks. The control systems chosen by museums depend on the size and age of the building, the financial means and the strategies that can be adapted. However, there is a lack of methods that can monitor mechanical changes or chemical reactions of objects in real-time or regularly. It would therefore ideally be preferable to monitor each of them to alert them to preserve them. For this purpose, a non-destructive, non-contact, full-field technique, Digital Holographic Speckle Pattern Interferometry (DHSPI), has already been developed and allows direct tracking of changes on the surface of artworks. This technique is based on phase-shifting speckle interferometry and gives the deformation of the surface below the level of the micro-meter of the analysed object. In order to monitor the deformation continuously, a large number of images are acquired by DHSPI and have to be processed. The existing process consists of removing noise from the interferogram, unwrapping this image, and deriving and displaying a 2D or 3D deformation map. In order to improve the time and accuracy of processing the imaging data, a simpler and faster processing method is developed. Using Matlab®, a denoising methodology for the interference pattern generated during data acquisition is created, based on a stationary wavelet transform. The unwrapped image is calculated using the CPULSI (Calibrated Phase Unwrapping based on Least-Squares and Iterations) algorithm as it gives the fastest results among the tested methods. The unwrapped phase is then transformed into surface displacement. This process performs these steps for each interferogram automatically. It allows access to 2D or 3D deformation maps.

Nonlocal means filter based on cosine similarity applied in speckle reduction of digital holography.

In the field of digital holography, the speckle caused by coherent light greatly disturbs the quality of the reconstruction. This paper presents an innovative method to efficiently reduce speckle noise with a nonlocal means filter based on cosine similarity that determines the weight of each traversal pixel to the target pixel by comparing the similarity between the target pixel neighborhood and the traversal pixel neighborhood. Experimental results with qualitative and quantitative analysis indicate that the proposed method significantly improves noise reduction performance while preserving the details of the original image. Compared with other general image-processing methods, this well-directed method is more in line with the characteristics of holographic speckle noise and has obvious advantages in various metrics.

A joint occultation and speckle investigation of the binary star TYC 1947-290-1 and of the asteroid (87) Sylvia

ABSTRACT We report on the occultation of the star TYC 1947-290-1 by the asteroid (87) Sylvia. While asteroidal occultations occurring at fixed professional-level locations are relatively rare and are only recently starting to be observed with sufficiently high time resolution and sensitivity, they have the capability to measure sub-milliarcsecond angular diameters. The event described here was especially outstanding because the star was revealed to be a small-separation binary (≈10 mas at discovery), while at the same time the asteroid is not only one of the largest in size but it also has two satellite moons. The observations were carried out at the Russian 6-m telescope in 2019 December, and initially consisted of both a fast photometric series of the occultation itself, as well as of extensive speckle interferometry of the star and asteroid in the time immediately before and after the occultation. Subsequently, we obtained speckle data of TYC 1947-290-1 over a period of 1 yr after the event. We are able to present a detailed study of the binary star including measurements of the angular diameter of the stellar components, their geometry, and relative fluxes over several bandpasses, and to provide an accurate determination of the size of (87) Sylvia. We emphasize that we have been able to obtain the smallest ever directly measured stellar diameter, below the 100 micro-arcsecond level. Our data are also suitable for imaging of the asteroid by speckle holography, a task which we intend to carry out in a separate work.

Dynamic Speckle Holography.

We introduce dynamic speckle holography, a new technique that combines imaging and scattering to measure three-dimensional maps of displacements as small as ten nanometers over several centimeters, greatly extending the capabilities of traditional imaging systems. We attain this sensitivity by imaging speckle patterns of light collected at three scattering angles and measuring the decay in the temporal correlation due to local motion. We use dynamic speckle holography to measure the strain field of a colloidal gel undergoing fracture and establish the surprising role of internal tension in driving the fracture.

Volumetric monitoring of airborne particulate matter concentration using smartphone-based digital holographic microscopy and deep learning

Airborne particulate matter (PM) has become a global environmental issue. This PM has harmful effects on public health and precision industries. Conventional air-quality monitoring methods usually utilize expensive equipment, and they are cumbersome to handle for accurate and high throughput measurements. In addition, commercial particle counters have technical limitations in high-concentration measurement, and data fluctuations are induced during air sampling. In this study, a novel smartphone-based technique for monitoring airborne PM concentrations was developed using smartphone-based digital holographic microscopy (S-DHM) and deep learning network called Holo-SpeckleNet. Holographic speckle images of various PM concentrations were recorded by the S-DHM system. The recorded speckle images and the corresponding ground truth PM concentrations were used to train deep learning algorithms consisting of a deep autoencoder and regression layers. The performance of the proposed smartphone-based PM monitoring technique was validated through hyperparameter optimization. The developed S-DHM integrated with Holo-SpeckleNet can be smartly and effectively utilized for portable PM monitoring and safety alarm provision under perilous environmental conditions.

Diffuser screen with flat-top angular distribution of scattered light realized by a dual-beam holographic speckle.

Holographic speckle screens with the Gaussian type distribution of scattered light, which are used to increase the viewing angle of the image in projection display systems, result in nonuniform image brightness in different observing positions. In this study, based on Helmholtz-Kirchhoff theory, a dual-beam scattering theory of rough surface is derived. By analyzing the spatial frequency spectrum of the scattered light, it is found that when two laser beams irradiated the ground glass at a certain angle, the resulting speckles recorded on the photoresist can generate a flat-top angular distribution of the scattered light. Speckle screens are fabricated by two light beams at different angles, and the angular intensity distribution of scattered light is measured. The results are in good agreement with the theory. Compared with the Gaussian type diffuser, the energy efficiency of the speckle screen proposed has a 46% increase when the angular luminance uniformity is set to be 80%, which effectively improves the brightness when used in a head up display system.

Accurate real-time monitoring of high particulate matter concentration based on holographic speckles and deep learning

Accurate real-time monitoring of particulate matter (PM) has emerged as a global issue due to the hazardous effects of PM on public health and industry. However, conventional PM monitoring techniques are usually cumbersome and require expensive equipments. In this study, Holo-SpeckleNet is proposed as a fast and accurate PM concentration measurement technique with high throughput using a deep learning based holographic speckle pattern analysis. Speckle pattern datasets of PMs for a wide range of PM concentrations were acquired by using a digital in-line holography microscopy system. Deep autoencoder and regression algorithms were trained with the captured speckle pattern datasets to directly measure PM concentration from speckle pattern images without any air intake device and time-consuming post image processing. The proposed technique was applied to predict various PM concentrations using the test datasets, optimize hyperparameters, and compare its performance with a convolutional neural network (CNN) algorithm. As a result, high PM concentration values can be measured over air quality index of 150, above which human exposure is unhealthy. In addition, the proposed technique exhibits higher measurement accuracy and less overfitting than the CNN with a relative error of 7.46 ± 3.92%. It can be applied to design a compact air quality monitoring device for highly accurate and real-time measurement of PM concentrations under hazardous environment, such as factories or construction sites.

Biodynamic digital holographic speckle microscopy for oocyte and embryo metabolic evaluation.

Assisted reproductive technologies seek to improve the success rate of pregnancies. Morphology scoring is a common approach to evaluate oocyte and embryo viability prior to embryo transfer in utero, but the efficacy of the method is low. We apply biodynamic imaging, based on dynamic light scattering and low-coherence digital holography, to assess the metabolic activity of oocytes and embryos. A biodynamic microscope, developed to image small and translucent biological specimens, is inserted into the bay of a commercial inverted microscope that can switch between conventional microscopy channels and biodynamic microscopy. We find intracellular Doppler spectral features that act as noninvasive proxies for embryo metabolic activity that may relate to embryo viability.

The Milky Way’s nuclear star cluster: Old, metal-rich, and cuspy

Context. The environment of Sagittarius A* (Sgr A*), the central black hole of the Milky Way, is the only place in the Universe where we can currently study the interaction between a nuclear star cluster and a massive black hole and infer the properties of a nuclear cluster from observations of individual stars. Aims. This work aims to explore the star formation history of the nuclear cluster and the structure of the innermost stellar cusp around Sgr A*. Methods. We combined and analysed multi epoch high quality AO observations. For the region close to Sgr A* we apply the speckle holography technique to the AO data and obtain images that are ≥50% complete down to Ks ≈ 19 within a projected radius of 5″ around Sgr A*. We used H-band images to derive extinction maps. Results. We provide Ks photometry for roughly 39 000 stars and H-band photometry for ∼11 000 stars within a field of about 40″ × 40″, centred on Sgr A*. In addition, we provide Ks photometry of ∼3000 stars in a very deep central field of 10″ × 10″, centred on Sgr A*. We find that the Ks luminosity function (KLF) is rather homogeneous within the studied field and does not show any significant changes as a function of distance from the central black hole on scales of a few 0.1 pc. By fitting theoretical luminosity functions to the KLF, we derive the star formation history of the nuclear star cluster. We find that about 80% of the original star formation took place 10 Gyr ago or longer, followed by a largely quiescent phase that lasted for more than 5 Gyr. We clearly detect the presence of intermediate-age stars of about 3 Gyr in age. This event makes up about 15% of the originally formed stellar mass of the cluster. A few percent of the stellar mass formed in the past few 100 Myr. Our results appear to be inconsistent with a quasi-continuous star formation history. The mean metallicity of the stars is consistent with being slightly super solar. The stellar density increases exponentially towards Sgr A* at all magnitudes between Ks = 15−19. We also show that the precise properties of the stellar cusp around Sgr A* are hard to determine because the star formation history suggests that the star counts can be significantly contaminated, at all magnitudes, by stars that are too young to be dynamically relaxed. We find that the probability of observing any young (non-millisecond) pulsar in a tight orbit around Sgr A* and beamed towards Earth is very low. We argue that typical globular clusters, such as they are observed in and around the Milky Way today, have probably not contributed to the nuclear cluster’s mass in any significant way. The nuclear cluster may have formed following major merger events in the early history of the Milky Way.

Deep Learning-Based Wrapped Phase Denoising Method for Application in Digital Holographic Speckle Pattern Interferometry

This paper presents a new processing method for denoising interferograms obtained by digital holographic speckle pattern interferometry (DHSPI) to serve in the structural diagnosis of artworks. DHSPI is a non-destructive and non-contact imaging method that has been successfully applied to the structural diagnosis of artworks by detecting hidden subsurface defects and quantifying the deformation directly from the surface illuminated by coherent light. The spatial information of structural defects is mostly delivered as local distortions interrupting the smooth distribution of intensity during the phase-shifted formation of fringe patterns. Distortions in fringe patterns are recorded and observed from the estimated wrapped phase map, but the inevitable electronic speckle noise directly affects the quality of the image and consequently the assessment of defects. An effective method for denoising DHSPI wrapped phase based on deep learning is presented in this paper. Although a related method applied to interferometry for reducing Gaussian noise has been introduced, it is not suitable for application in DHSPI to reduce speckle noise. Thus, the paper proposes a new method to remove speckle noise in the wrapped phase. Simulated data and experimental captured data from samples prove that the proposed method can effectively reduce the speckle noise of the DHSPI wrapped phase to extract the desired information. The proposed method is helpful for accurately detecting defects in complex defect topography maps and may help to accelerate defect detection and characterization procedures.

Speckle Holography of Visual Double Stars at the 2.1 m Telescope of OAN-SPM: First Results

Abstract We present our first results of multiband Speckle Holography of components of visual double stars. The observations were performed during 2019 April at the 2.1 m telescope at the Observatorio Astronómico Nacional at Sierra de San Pedro Mártir (México). We have observed 190 double stars with separation between 3″ and 5″. The position angle, separation and magnitude difference in three broadband optical filters (VRI) for these systems are provided. For 15 systems we found different interesting features, we have identified a close component for 9 of those systems; 5 of them are newly discovered. In the remaining 6 systems, although unresolved, we found elongations that we have been able to derive astrometric parameters if proven to be a (newly discovered) close component. This corresponds to about 8% of the sample presenting a certain feature in one of the components and about 5% of the sample having a confirmed close component.

СОВРЕМЕННЫЕ ИНТЕРФЕРЕНЦИОННО-ОПТИЧЕСКИЕ ТЕХНОЛОГИИ ИССЛЕДОВАНИЯ И НЕРАЗРУШАЮЩЕГО КОНТРОЛЯ НЕОДНОРОДНЫХ КОНСТРУКЦИЙ (ОБЗОР)

Рассматривается состояние технологий исследования и неразрушающего контроля прочностных и динамических свойств неоднородных конструкций на основе голографической интерферометрии, спекл-интерферометрии, высококогерентной и низкокогерентной классической интерферометрии. Приведены их особенности, области эффективного применения.

Computational cytometer based on magnetically modulated coherent imaging and deep learning

Detecting rare cells within blood has numerous applications in disease diagnostics. Existing rare cell detection techniques are typically hindered by their high cost and low throughput. Here, we present a computational cytometer based on magnetically modulated lensless speckle imaging, which introduces oscillatory motion to the magnetic-bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three dimensions (3D). In addition to using cell-specific antibodies to magnetically label target cells, detection specificity is further enhanced through a deep-learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. To demonstrate the performance of this technique, we built a high-throughput, compact and cost-effective prototype for detecting MCF7 cancer cells spiked in whole blood samples. Through serial dilution experiments, we quantified the limit of detection (LoD) as 10 cells per millilitre of whole blood, which could be further improved through multiplexing parallel imaging channels within the same instrument. This compact, cost-effective and high-throughput computational cytometer can potentially be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.

Consistency of the Infrared Variability of SGR A* over 22 yr

Abstract We report new infrared (IR) measurements of the supermassive black hole at the Galactic Center, Sgr A*, over a decade that was previously inaccessible at these wavelengths. This enables a variability study that addresses variability timescales that are 10 times longer than earlier published studies. Sgr A* was initially detected in the near-infrared (NIR) with adaptive optics observations in 2002. While earlier data exists in form of speckle imaging (1995–2005), Sgr A* was not detected in the initial analysis. Here, we improved our speckle holography analysis techniques. This has improved the sensitivity of the resulting speckle images by up to a factor of three. Sgr A* is now detectable in the majority of epochs covering 7 yr. The brightness of Sgr A* in the speckle data has an average observed K magnitude of 16.0, which corresponds to a dereddened flux density of 3.4 mJy. Furthermore, the flat power spectral density of Sgr A* between ∼80 days and 7 yr shows its uncorrelation in time beyond the proposed single power-law break of ∼245 minutes. We report that the brightness and its variability is consistent over 22 yr. This analysis is based on simulations using the Witzel et al. model to characterize IR variability from 2006 to 2016. Finally, we note that the 2001 periapse of the extended, dusty object G1 had no apparent effect on the NIR emission from accretion flow onto Sgr A*. The result is consistent with G1 being a self-gravitating object rather than a disrupting gas cloud.