Strategies for reducing speckle noise in digital holography

Continuous-wave degenerate cavity laser for optical imaging in scattering media

Lasers play a significant role in optical communication, medical, and scientific research, owing to their high brightness and high coherence. However, the high spatial coherence will lead to specific challenges, such as speckle noise in imaging and wavefront distortion during propagation through scattering media. Here, a continuous-wave (cw) degenerate cavity laser (DCL) with low spatial coherence is demonstrated with efficient suppression of the thermal lensing effect from the gain crystal. Experimentally, a cw degenerate laser output with about 2000 transverse modes corresponding to a speckle contrast of about 0.0224 is achieved. This laser can be used for speckle reduction and is robust against atmospheric turbulence, which may find applications in the field of laser imaging technology and illumination.

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.

Technology Selection for Inline Topography Measurement with Rover-Borne Laser Spectrometers

This work studies enhancing the capabilities of compact laser spectroscopes integrated into space-exploration rovers by adding 3D topography measurement techniques. Laser spectroscopy enables the in situ analysis of sample composition, aiding in the understanding of the geological history of extraterrestrial bodies. To complement spectroscopic data, the inclusion of 3D imaging is proposed to provide unprecedented contextual information. The morphological information aids material characterization and hence the constraining of rock and mineral histories. Assigning height information to lateral pixels creates topographies, which offer a more complete spatial dataset than contextual 2D imaging. To aid the integration of 3D measurement into future proposals for rover-based laser spectrometers, the relevant scientific, rover, and sample constraints are outlined. The candidate 3D technologies are discussed, and estimates of performance, weight, and power consumptions guide the down-selection process in three application examples. Technology choice is discussed from different perspectives. Inline microscopic fringe-projection profilometry, incoherent digital holography, and multiwavelength digital holography are found to be promising candidates for further development.

One step accurate phase demodulation from a closed fringe pattern with the convolutional neural network HRUnet

Retrieving a phase map from a single closed fringe pattern is a challenging task in optical interferometry. In this paper, a convolutional neural network (CNN), HRUnet, is proposed to demodulate phase from a closed fringe pattern. The HRUnet, derived from the Unet model, adopts a high resolution network (HRnet) module to extract high resolution feature maps of the data and employs residual blocks to erase the gradient vanishing in the network. With the trained network, the unwrapped phase map can be directly obtained by feeding a scaled fringe pattern. The high accuracy of the phase map obtained from HRUnet is demonstrated by demodulation of both simulated data and actual fringe patterns. Compared results between HRUnet and two other CNNS are also provided, and the results proved that the performance of HRUnet in accuracy is superior to the two other counterparts.

Liquid lens based holographic camera for real 3D scene hologram acquisition using end-to-end physical model-driven network

With the development of artificial intelligence, neural network provides unique opportunities for holography, such as high fidelity and dynamic calculation. How to obtain real 3D scene and generate high fidelity hologram in real time is an urgent problem. Here, we propose a liquid lens based holographic camera for real 3D scene hologram acquisition using an end-to-end physical model-driven network (EEPMD-Net). As the core component of the liquid camera, the first 10 mm large aperture electrowetting-based liquid lens is proposed by using specially fabricated solution. The design of the liquid camera ensures that the multi-layers of the real 3D scene can be obtained quickly and with great imaging performance. The EEPMD-Net takes the information of real 3D scene as the input, and uses two new structures of encoder and decoder networks to realize low-noise phase generation. By comparing the intensity information between the reconstructed image after depth fusion and the target scene, the composite loss function is constructed for phase optimization, and the high-fidelity training of hologram with true depth of the 3D scene is realized for the first time. The holographic camera achieves the high-fidelity and fast generation of the hologram of the real 3D scene, and the reconstructed experiment proves that the holographic image has the advantage of low noise. The proposed holographic camera is unique and can be used in 3D display, measurement, encryption and other fields.

Hologram Noise Model for Data Augmentation and Deep Learning

This paper introduces a noise augmentation technique designed to enhance the robustness of state-of-the-art (SOTA) deep learning models against degraded image quality, a common challenge in long-term recording systems. Our method, demonstrated through the classification of digital holographic images, utilizes a novel approach to synthesize and apply random colored noise, addressing the typically encountered correlated noise patterns in such images. Empirical results show that our technique not only maintains classification accuracy in high-quality images but also significantly improves it when given noisy inputs without increasing the training time. This advancement demonstrates the potential of our approach for augmenting data for deep learning models to perform effectively in production under varied and suboptimal conditions.

Method for Measuring the Three-Dimensional Morphology of Near-Wall Bubbles and Droplets Based on LED Digital Holography

Digital holography, recognized for its noncontact nature and high precision in three-dimensional imaging, is effectively employed to measure the morphology of bubbles and droplets. However, in terms of near-wall bubbles and droplets, such as confined bubbles in microfluidic chips, the measurement of the interface morphology of bubbles near the glass surface has not yet been resolved due to the coherent noise resulting from glass surface reflections in microfluidic chips. Accordingly, an off-axis digital holography system was devised by using Linnik interferometry. Measuring the confined bubble interface near the wall within a microfluidic chip and droplet evaporation on solid surfaces was studied. Partially coherent LED sources and reference light modulation techniques were employed in the optical setup to mitigate the coherent noise. Dual exposure and weighted least-squares unwrapping algorithms were introduced to correct phase distortions, enhancing image quality. Imaging two confined CO2 bubbles was done near the wall in silicon oil within a porous microfluidic chip, and contact angles of 4.7 and 4.5° were measured. Additionally, the measurement of the three-dimensional morphology of vertically evaporating deionized water droplets on a glass surface was done, due to which calculation of contact angles at various orientations was possible. This work offers a feasible new method for measuring the 3D interface morphology of bubbles and droplets, particularly in microfluidic visualization, addressing current measurement gaps.

Influence of wavelength, linewidth, and temperature on second harmonic generation of a superfluorescent fiber source

Low-coherence tunable visible light sources have a wide range of applications in imaging, spectroscopy, medicine, and so on. Second harmonic generation (SHG) based on a superfluorescent fiber source (SFS) can produce high-brightness visible light while retaining most of the characteristics of superfluorescent sources, such as low coherence, low intensity noise and flexible tunability. However, due to the limitations in phase matching conditions, SHG based on SFS is difficult to reach an equilibrium between high efficiency and robustness of phase matching to temperature variation. In this paper, based on a spectral tunable SFS, we provide a comprehensive analysis, both experimental and theoretical, of the impact of wavelength, linewidth, and temperature on the output performance of SHG. Our findings indicate that broader linewidths adversely affect conversion efficiency, yet they enhance the capacity to withstand temperature variations and central wavelength detuning, which is an advantage that traditional SHG methods do not possess. This work may pave the way for utilizing low-coherence visible light in domains and extreme environments where robust output stability becomes imperative.

High-axial-resolution speckle-free holographic reconstruction via cylindrical quadratic phase method and temporal focusing

Holographic techniques enable precise laser manipulation, but suffer from two considerable limitations: speckle and deterioration of axial distribution. Here, we propose a cylindrical quadratic phase (CQP) method with temporal focusing (TF) to generate speckle-free holographic illumination with high axial resolution. TF-CQP utilizes a superposed cylindrical phase as the initial guess to iteratively optimize phase hologram, realizing speckle-free holographic reconstruction on the target focal plane and eliminating secondary focus on the defocused planes. TF-CQP further disperses defocused beams symmetrically by a blazed grating, placed conjugate to the focal plane, which enhances axial confinement. Simulation and experimental results show that TF-CQP reconstructs speckle-free illumination with arbitrary shapes and <10 µm axial resolution. Compared to TF-GS (Gerchberg-Saxton algorithm), widely used in holographic optogenetics, TF-CQP shows increased uniformity of 200% and improved modulation efficiency of 32.33% for parallel holographic illumination, as well as a 10% increment in axial resolution.

Noise reduction in digital holography phase maps by phase-preserving discrete Fourier resampling

Several methods have been proposed to reduce the detrimental effects of coherent noise in holographic imaging. Among them, the use of spatial-frequency masking or resampling has been widely applied because of its low implementation complexity and well-studied trade-off between denoising effectiveness and spatial resolution. While the digital application of this method has been successfully demonstrated for intensity images, its application to phase maps fails. This work shows that the phase applicability of these methods depends on the use of resampling masks that strictly keep the zero-order spatial frequencies. Alternative masks are proposed that demonstrate effective single-shot noise reduction in experimental phase maps from digital holographic microscopy. The resulting method is potentially extendable to any other complex-valued-field retrieval technique.

Meta-holograms under incoherent illumination: image properties and spackle pattern

We study the properties of the images projected by meta-holograms under broadband incoherent/polychromatic illumination. We show that despite the broadband illumination, some of the coherent properties of the images such as the speckle pattern are retained even for sources with bandwidth of 20 nm. We study the projected images and their speckle pattern properties under various illumination spectra using a set of monochromatic images obtained at different wavelengths.

Photolithographic patterning on multi-wavelength quantum dot film of the improved conversion efficiency for digital holography

A triple-wavelength patterned quantum dot film was fabricated for the light source of digital holography to improve both the axial measurement range and noise reduction. The patterned quantum dot film was fabricated after optimizing the photolithography process condition based on the UV-curable quantum dot solution, which was capable of multiple patterning processes. In addition, an optimized pattern structure was developed by adding TiO2 nanoparticles to both the quantum dot and bank layers to increase the scattering effect for the improved photoluminescence intensity. Finally, the newly developed light source with the balanced spectral distribution was applied to the digital holography, rendering it applicable as an improved light source.

Diffuse-illumination holographic optical coherence tomography

Holographic optical coherence tomography (OCT) is a powerful imaging technique, but its ability to reveal low-reflectivity features is limited. In this study, we performed holographic OCT by incoherently averaging volumes with changing diffuse illumination of numerical aperture (NA) equal to the detection NA. While the reduction of speckle from singly scattered light is only modest, we discovered that speckle from multiply scattered light can be arbitrarily reduced, resulting in substantial improvements in image quality. This technique also offers the advantage of suppressing noises arising from spatial coherence, and can be implemented with a partially spatially incoherent light source for further mitigation of multiple scattering. Finally, we show that although holographic reconstruction capabilities are increasingly lost with decreasing spatial coherence, they can be retained over an axial range sufficient to standard OCT applications.

Zwitterion-doped liquid crystal speckle reducers for immersive displays and vectorial imaging

Lasers possess many attractive features (e.g., high brightness, narrow linewidth, well-defined polarization) that make them the ideal illumination source for many different scientific and technological endeavors relating to imaging and the display of high-resolution information. However, their high-level of coherence can result in the formation of noise, referred to as speckle, that can corrupt and degrade images. Here, we demonstrate a new electro-optic technology for combatting laser speckle using a chiral nematic liquid crystal (LC) dispersed with zwitterionic dopants. Results are presented that demonstrate when driven at the optimum electric field conditions, the speckle noise can be reduced by >90% resulting in speckle contrast (C) values of C = 0.07, which is approaching that required to be imperceptible to the human eye. This LC technology is then showcased in an array of different display and imaging applications, including a demonstration of speckle reduction in modern vectorial laser-based imaging.

Fast Hologram Calculation Method Based on Wavefront Precise Diffraction

In this paper, a fast hologram calculation method based on wavefront precise diffraction is proposed. By analyzing the diffraction characteristics of the object point on the 3D object, the effective viewing area of the reproduced image is analyzed. Based on the effective viewing area, the effective hologram size of the object point is obtained, and then the accurate diffraction calculation from the object point to the wavefront recording plane (WRP) is performed. By calculating all the object points on the recorded object, the optimized WRP of the whole 3D object can be obtained. The final hologram is obtained by calculating the diffraction light field from the WRP to the holographic plane. Compared with the traditional method, the proposed method can improve the calculation speed by more than 55%, while the image quality of the holographic 3D display is not affected. The proposed calculation method provides an idea for fast calculation of holograms and is expected to contribute to the development of dynamic holographic displays.

Speckle suppression in arbitrary parallel holographic illumination by the spatial frequency regaining method

This Letter proposes a spatial frequency regaining method for parallel holographic illumination (SFR-PHI) to suppress speckle noise in phase-only computer-generated holography (CGH). Based on the accurate calculation of the beam bandwidth, this method uses the bandwidth-limited quadratic initial phase and weighted constraint iteration to generate the optimized phase hologram, which can provide the accurate spatial frequency of multiple illumination patterns. The results show that SFR-PHI performs superiorly in speckle suppression for generating dozens of illumination patterns in parallel and with arbitrary shapes and numbers. Compared with other speckle-suppression methods, it exhibits significant advantages in terms of accuracy and modulation efficiency.

3D incoherent imaging using an ensemble of sparse self-rotating beams

Interferenceless coded aperture correlation holography (I-COACH) is one of the simplest incoherent holography techniques. In I-COACH, the light from an object is modulated by a coded mask, and the resulting intensity distribution is recorded. The 3D image of the object is reconstructed by processing the object intensity distribution with the pre-recorded 3D point spread intensity distributions. The first version of I-COACH was implemented using a scattering phase mask, which makes its implementation challenging in light-sensitive experiments. The I-COACH technique gradually evolved with the advancement in the engineering of coded phase masks that retain randomness but improve the concentration of light in smaller areas in the image sensor. In this direction, I-COACH was demonstrated using weakly scattered intensity patterns, dot patterns and recently using accelerating Airy patterns, and the case with accelerating Airy patterns exhibited the highest SNR. In this study, we propose and demonstrate I-COACH with an ensemble of self-rotating beams. Unlike accelerating Airy beams, self-rotating beams exhibit a better energy concentration. In the case of self-rotating beams, the uniqueness of the intensity distributions with depth is attributed to the rotation of the intensity pattern as opposed to the shifts of the Airy patterns, making the intensity distribution stable along depths. A significant improvement in SNR was observed in optical experiments.

Deep learning-based incoherent holographic camera enabling acquisition of real-world holograms for holographic streaming system

While recent research has shown that holographic displays can represent photorealistic 3D holograms in real time, the difficulty in acquiring high-quality real-world holograms has limited the realization of holographic streaming systems. Incoherent holographic cameras, which record holograms under daylight conditions, are suitable candidates for real-world acquisition, as they prevent the safety issues associated with the use of lasers; however, these cameras are hindered by severe noise due to the optical imperfections of such systems. In this work, we develop a deep learning-based incoherent holographic camera system that can deliver visually enhanced holograms in real time. A neural network filters the noise in the captured holograms, maintaining a complex-valued hologram format throughout the whole process. Enabled by the computational efficiency of the proposed filtering strategy, we demonstrate a holographic streaming system integrating a holographic camera and holographic display, with the aim of developing the ultimate holographic ecosystem of the future.

Bragg degenerate model for fabrication of holographic waveguide-based near-eye displays

The coupling efficiency of light beams is a crucial factor for waveguide displays. Generally, the light beam is not coupled with maximum efficiency in the holographic waveguide without employing a prism in the recording geometry. Use of prisms in recording geometry leads to restricting the propagation angle of the waveguide to a specific value only. The issue of efficient coupling of a light beam without using prisms could be overcome via Bragg degenerate configuration. In this work, the simplified expressions of the Bragg degenerate case are obtained for the realization of normally illuminated waveguide-based displays. Using this model, by tuning the parameters of recording geometry, a range of propagation angles can be produced for a fixed normal incidence of a playback beam. Numerical simulations and experimental investigations of the Bragg degenerate waveguides of different geometries are performed to validate the model. A Bragg degenerate playback beam is successfully coupled in four waveguides recorded with different geometries and yields good diffraction efficiency at normal incidence. The quality of transmitted images is characterized using the structural similarity index measure. The augmentation of a transmitted image in the real world is experimentally demonstrated through the fabricated holographic waveguide for near-eye display applications. Bragg degenerate configuration can provide flexibility in the angle of propagation while maintaining the same coupling efficiency achievable with a prism for holographic waveguide displays.

Label-free high-resolution white light quantitative phase nanoscopy system

We present a high-resolution white light quantitative phase nanoscopy (WLQPN) system that can be utilized to visualize nanoparticles and subcellular features of the biological specimens. The five-phase shifting technique, along with deconvolution, is adopted to obtain super-resolution in phase imaging. The phase shifting technique can provide full detector resolution, making it beneficial as compared to the well-known Fourier analysis method. The Fourier transform method requires minimum angle of sin - 1 3 f x λ , where f x is maximum achievable spatial frequency. It limits the highest achievable resolution to much below the actual diffraction limit of the system. Thus, to obtain a high-resolution phase map of the biological specimen, a two-step process is adopted. First, the phase map is recovered using the five-phase shifting algorithm, with full detector spatial resolution. Second, the complex field is obtained from the recovered phase map and further processed using the Richardson Lucy total variation deconvolution algorithm to obtain super-resolution phase images. The present technique was tested on 1951 USAF resolution chart, 200 nm polystyrene beads and Escherichia coli bacteria using a 50×, 0.55NA objective lens. The 200 nm polystyrene beads are visually resolvable and subcellular features of the E. coli bacteria are also observed, suggesting a significant improvement in the resolution.

Digital holographic approaches to the detection and characterization of microplastics in water environments

Microplastic (MP) pollution is seriously threatening the environmental health of the world, which has accelerated the development of new identification and characterization methods. Digital holography (DH) is one of the emerging tools to detect MPs in a high-throughput flow. Here, we review advances in MP screening by DH. We examine the problem from both the hardware and software viewpoints. Automatic analysis based on smart DH processing is reported by highlighting the role played by artificial intelligence for classification and regression tasks. In this framework, the continuous development and availability in recent years of field-portable holographic flow cytometers for water monitoring also is discussed.

The color of aerosol particles

Digital in-line holography (DIH) is an established method to image small particles in a manner where image reconstruction is performed computationally post-measurement. This ability renders it ideal for aerosol characterization, where particle collection or confinement is often difficult, if not impossible. Conventional DIH provides a gray-scale image akin to a particle's silhouette, and while it gives the particle size and shape, there is little information about the particle material. Based on the recognition that the spectral reflectance of a surface is partly determined by the material, we demonstrate a method to image free-flowing particles with DIH in color with the eventual aim to differentiate materials based on the observed color. Holograms formed by the weak backscattered light from individual particles illuminated by red, green, and blue lasers are recorded by a color sensor. Images are reconstructed from the holograms and then layered to form a color image, the color content of which is quantified by chromaticity analysis to establish a representative signature. A variety of mineral dust aerosols are studied where the different signatures suggest the possibility to differentiate particle material. The ability of the method to resolve the inhomogeneous composition within a single particle in some cases is shown as well.

Multicolor detour phase holograms based on an Al plasmonic color filter

The remarkable advances in nanofabrication that have occurred over the last decade present opportunities for the realization of new types of holograms. In this work, for the first time to the best of our knowledge, a method for phase multicolor holograms based on nanohole arrays is described. The nanoholes are in an aluminum film that is interposed between the glass substrate and a silicon dioxide layer. The nanoholes serve as color filters for blue, green, and red wavelengths and provide the necessary phase distribution via the detour phase method. Our nanohole arrays are optimized to maximize the transmission efficiency of the red, green, and blue channels and to minimize the cross-talk between them. We design two multicolor holograms based on these filters and simulate their performance. The results show good fidelity to the desired holographic images. The proposed structure has the advantages of being very compact, of requiring only a simple fabrication method with one lithography step, and of employing materials (aluminum and silicon dioxide) that are compatible with standard CMOS technology.

Tuning Axial Resolution Independent of Lateral Resolution in a Computational Imaging System Using Bessel Speckles

Speckle patterns are formed by random interferences of mutually coherent beams. While speckles are often considered as unwanted noise in many areas, they also formed the foundation for the development of numerous speckle-based imaging, holography, and sensing technologies. In the recent years, artificial speckle patterns have been generated with spatially incoherent sources using static and dynamic optical modulators for advanced imaging applications. In this report, a basic study has been carried out with Bessel distribution as the fundamental building block of the speckle pattern (i.e., speckle patterns formed by randomly interfering Bessel beams). In general, Bessel beams have a long focal depth, which in this scenario is counteracted by the increase in randomness enabling tunability of the axial resolution. As a direct imaging method could not be applied when there is more than one Bessel beam, an indirect computational imaging framework has been applied to study the imaging characteristics. This computational imaging process consists of three steps. In the first step, the point spread function (PSF) is calculated, which is the speckle pattern formed by the random interferences of Bessel beams. In the next step, the intensity distribution for an object is obtained by a convolution between the PSF and object function. The object information is reconstructed by processing the PSF and the object intensity distribution using non-linear reconstruction. In the computational imaging framework, the lateral resolution remained a constant, while the axial resolution improved when the randomness in the system was increased. Three-dimensional computational imaging with statistical averaging for different cases of randomness has been synthetically demonstrated for two test objects located at two different distances. The presented study will lead to a new generation of incoherent imaging technologies.

LED based large field of view off-axis quantitative phase contrast microscopy by hologram multiplexing

In this manuscript, we describe the development of a single shot, self-referencing wavefront division, multiplexing digital holographic microscope employing LED sources for large field of view quantitative phase imaging of biological samples. To address the difficulties arising while performing interferometry with low temporally coherent sources, an optical arrangement utilizing multiple Fresnel Biprisms is used for hologram multiplexing, enhancing the field of view and increasing the signal to noise ratio. Biprisms offers the ease of obtaining interference patterns by automatically matching the path length between the two off-axis beams. The use of low temporally coherent sources reduces the speckle noise and the cost, and the form factor of the setup. The developed technique was implemented using both visible and UV LEDs and tested on polystyrene microspheres and human erythrocytes.

Real-time 3D imaging of ocean algae with crosstalk suppressed single-shot digital holographic microscopy

Digital holographic microscopy (DHM) has the potential to reconstruct the 3D shape of volumetric samples from a single-shot hologram in a label-free and noninvasive manner. However, the holographic reconstruction is significantly compromised by the out-of-focus image resulting from the crosstalk between refocused planes, leading to the low fidelity of the results. In this paper, we propose a crosstalk suppression algorithm-assisted 3D imaging method combined with a home built DHM system to achieve accurate 3D imaging of ocean algae using only a single hologram. As a key step in the algorithm, a hybrid edge detection strategy using gradient-based and deep learning-based methods is proposed to offer accurate boundary information for the downstream processing. With this information, the crosstalk of each refocused plane can be estimated with adjacent refocused planes. Empowered by this method, we demonstrated successful 3D imaging of six kinds of ocean algae that agree well with the ground truth; we further demonstrated that this method could achieve real-time 3D imaging of the quick swimming ocean algae in the water environment. To our knowledge, this is the first time single-shot DHM is reported in 3D imaging of ocean algae, paving the way for on-site monitoring of the ocean algae.

Review of computer-generated hologram algorithms for color dynamic holographic three-dimensional display

Holographic three-dimensional display is an important display technique because it can provide all depth information of a real or virtual scene without any special eyewear. In recent years, with the development of computer and optoelectronic technology, computer-generated holograms have attracted extensive attention and developed as the most promising method to realize holographic display. However, some bottlenecks still restrict the development of computer-generated holograms, such as heavy computation burden, low image quality, and the complicated system of color holographic display. To overcome these problems, numerous algorithms have been investigated with the aim of color dynamic holographic three-dimensional display. In this review, we will explain the essence of various computer-generated hologram algorithms and provide some insights for future research.

Method of color holographic display with speckle noise suppression

In this paper, a method of color holographic display with speckle noise suppression is proposed. Firstly, the intensity information of the object is extracted according to the red, green and blue (RGB) channels. The band-limited phase is calculated and used as the initial phase for each color channel. Secondly, the double-step Fresnel diffraction algorithm is used to calculate the computer-generated holograms (CGHs), and a filter plane that dynamically adjusts the position of the filter in the optical path is designed. Then, a divergent spherical phase factor is added to the CGHs. Finally, the time average method is used to further reduce the speckle noise. When the CGHs of the RGB channels are loaded on the digital micromirror device and illuminated by the RGB lights emitting in a temporal sequence, the color reconstructed images with speckle noise suppression can be displayed. The validity of the proposed method is verified.

Convex optimization for additive noise reduction in quantitative complex object wave retrieval using compressive off-axis digital holographic imaging

Image denoising is one of the important problems in the research field of computer vision, artificial intelligence, 3D vision, and image processing, where the fundamental aim is to recover the original image features from a noisy contaminated image. The camera sensor additive noise present in the holographic recording process reduces the quality of the retrieved image. Even though various techniques have been developed to minimize the noise in digital holography, the noise reduction still remains a challenging task. This article presents a compressive sensing (CS) technique to minimize the additive noise in the digital holographic reconstruction process. We demonstrate the reduction of additive noise using complex wave retrieval method as a sensing matrix in the CS model. The proposed CS method to suppress the noise during the reconstruction process is illustrated using numerical simulations. Only 50% of the pixel measurements are considered in the noisy hologram, which is far less than the original complex object pixels. The impact of additive gaussian noise in the recording plane on the reconstruction accuracy of both intensity and phase distribution is analysed. The CS method denoises and estimates the complex object information accurately. The numerical simulation results have shown that the proposed CS method has effectively minimized the noise in the reconstructed image and has greatly improved the quality of both intensity and phase information.

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.

Wide-Field Super-Resolution Optical Fluctuation Imaging through Dynamic Near-Field Speckle Illumination

Stochastic optical fluctuation imaging (SOFI) generates super-resolution fluorescence images by emphasizing the positions of fluorescent emitters via statistical analysis of their on-and-off blinking dynamics. In SOFI with speckle illumination (S-SOFI), the diffraction-limited grain size of the far-field speckles prevents independent blinking of closely located emitters, becoming a hurdle to realize the full super-resolution granted by SOFI processing. Here, we present a surface-sensitive super-resolution technique exploiting dynamic near-field speckle illumination to bring forth the full super-resolving power of SOFI without blinking fluorophores. With our near-field S-SOFI technique, up to 2.8- and 2.3-fold enhancements in lateral spatial resolution are demonstrated with computational and experimental fluorescent test targets labeled with conventional fluorophores, respectively. Fluorescent beads separated by 175 nm are also super-resolved by near-field speckles of 150 nm grain size, promising sub-100 nm resolution with speckle patterns of much smaller grain size.

Deep learning in optical metrology: a review

With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, nondestructive testing, experimental mechanics, and biomedicine. In recent years, deep learning, a subfield of machine learning, is emerging as a powerful tool to address problems by learning from data, largely driven by the availability of massive datasets, enhanced computational power, fast data storage, and novel training algorithms for the deep neural network. It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology. Unlike the traditional "physics-based" approach, 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. In this review, we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology. We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning, followed by a comprehensive review of its applications in various optical metrology tasks, such as fringe denoising, phase retrieval, phase unwrapping, subset correlation, and error compensation. The open challenges faced by the current deep-learning approach in optical metrology are then discussed. Finally, the directions for future research are outlined.

Laser fabrication and evaluation of holographic intrinsic physical unclonable functions

Optical Physical Unclonable Functions (PUFs) are well established as the most powerful anticounterfeiting tool. Despite the merits of optical PUFs, widespread use is hindered by existing implementations that are complicated and expensive. On top, the overwhelming majority of optical PUFs refer to extrinsic implementations. Here we overcome these limitations to demonstrate for the first time strong intrinsic optical PUFs with exceptional security characteristics. In doing so, we use Computer-Generated Holograms (CGHs) as optical, intrinsic, and image-based PUFs. The required randomness is offered by the non-deterministic fabrication process achieved with industrial friendly, nanosecond pulsed fiber lasers. Adding to simplicity and low cost, the digital fingerprint is derived by a setup which is designed to be adjustable in a production line. In addition, we propose a novel signature encoding and authentication mechanism that exploits manifold learning techniques to efficiently differentiate data reconstruction-related variation from counterfeit attacks. The proposed method is applied experimentally on silver plates. The robustness of the fabricated intrinsic optical PUFs is evaluated over time. The results have shown exceptional values for robustness and a probability of cloning up to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^{-14}$$\end{document}10-14, which exceeds the standard acceptance rate in security applications.

Range selective digital holographic imaging using FMCW lidar

The integration of chirped frequency modulated continuous wave (FMCW) lidar techniques into digital holography enables range selective holographic imaging well beyond the depth of field of the system. The technique uses FMCW transmit and reference beams. By frequency shifting the reference beam to compensate for the typical FMCW beat frequency associated with a particular range, temporally stable holograms are formed for objects at the selected range. The holograms associated with objects at all other ranges oscillate and integrate towards zero. Experimental demonstrations of the technique are presented, showing enhanced imaging of objects at different ranges and cancellation of obscuring objects. The technique is expandable to range-Doppler selective digital holographic imaging.

Noise free defect detection in ceramic tableware using a portable digital holographic camera

This paper describes detection of cracks in ceramic tableware using a portable digital holographic camera working on the principle of double-exposure digital holographic interferometry. Digital image processing techniques are applied on amplitude and phase information obtained from the numerically reconstructed wavefronts of the test object to locate position of the defect. Speckles generated due to illumination of the rough surface of the ceramic cup with the coherent light source deteriorate quality of the interferometric phase. Several iterations of the averaging filter with optimized kernel size are applied on sine and cosine components of the interferometric phase to minimize the speckle noise. The effect of kernel size of the matrix used in the averaging filter on quality of the interferometric phase is analyzed by evaluating the signal-to-noise ratio. The experimentally obtained size of crack on a ceramic cup (0.08 mm) is validated by a mechanical profiler with an error of 6.6%. This study may help in improving the quality criteria of tableware items.

Backscatter multiple wavelength digital holography for color micro-particle imaging

This work applies digital holography to image stationary micro-particles in color. The approach involves a Michelson interferometer to mix reference light with the weak intensity light backscattered from a distribution of particles. To enable color images, three wavelengths are used, 430, 532, and 633 nm, as primary light sources. Three separate backscattered holograms are recorded simultaneously, one for each wavelength, which are resolved without spectral cross talk using a three-CMOS prism sensor. Fresnel diffraction theory is used to render monochrome images from each hologram. The images are then combined via additive color mixing with red, green, and blue as the primary colors. The result is a color image similar in appearance to that obtained with a conventional microscope in white-light epi-illumination mode. A variety of colored polyethylene micro-spheres and nonspherical dust particles demonstrate the feasibility of the approach and illustrate the effect of simple speckle-noise suppression and white balance methods. Finally, a chromaticity analysis is applied that is capable of differentiating particles of different colors in a quantitative and objective manner.

Computational multi-wavelength phase synthesis using convolutional neural networks [Invited]

Multi-wavelength digital holographic microscopy (MWDHM) provides indirect measurements of the refractive index for non-dispersive samples. Successive-shot MWDHM is not appropriate for dynamic samples and single-shot MWDHM significantly increases the complexity of the optical setup due to the need for multiple lasers or a wavelength tunable source. Here we consider deep learning convolutional neural networks for computational phase synthesis to obtain high-speed simultaneous phase estimates on different wavelengths and thus single-shot estimates of the integral refractive index without increased experimental complexity. This novel, to the best of our knowledge, computational concept is validated using cell phantoms consisting of internal refractive index variations representing cytoplasm and membrane-bound organelles, respectively, and a simulation of a realistic holographic recording process. Specifically, in this work we employed data-driven computational techniques to perform accurate dual-wavelength hologram synthesis (hologram-to-hologram prediction), dual-wavelength phase synthesis (unwrapped phase-to-phase prediction), direct phase-to-index prediction using a single wavelength, hologram-to-phase prediction, and 2D phase unwrapping with sharp discontinuities (wrapped-to-unwrapped phase prediction).

Elimination of abnormal phase fluctuation in digital holography

In digital holography, the phase is most important, and the quality of the reconstructed phase determines the final reconstructed image effect. However, noise is inevitably introduced in the process of recording the hologram. For regions without object light, the phase has a random distribution, which affects the final phase quality. This kind of noise is called abnormal phase fluctuations in this paper. The correlation between amplitude and phase in digital holography is used to judge whether there is useful phase information. Through structural similarity and the light-dark relationship, a credible probability mask is introduced to extract the phase that needs to be preserved. The simulation and experimental results show that abnormal phase fluctuations are successfully removed, and the useful phase information is retained.

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.

Multiple-scattering suppressive refractive index tomography for the label-free quantitative assessment of multicellular spheroids

Refractive index (RI) tomography is a quantitative tomographic technique used to visualize the intrinsic contrast of unlabeled biological samples. Conventional RI reconstruction algorithms are based on weak-scattering approximation, such as the Born or Rytov approximation. Although these linear algorithms are computationally efficient, they are invalid when the fields are strongly distorted by multiple scattering (MS) of specimens. Herein, we propose an approach to reconstruct the RI distributions of MS objects even under weak-scattering approximation using an MS-suppressive operation. The operation converts the distorted fields into MS-suppressed fields, where weak-scattering approximation is applicable. Using this approach, we reconstructed a whole multicellular spheroid and successfully visualized its internal subcellular structures. Our work facilitates the realization of RI tomography of MS specimens and label-free quantitative analysis of 3D multicellular specimens.

Linearity and Optimum-Sampling in Photon-Counting Digital Holographic Microscopy

In the image plane configurations frequently used in digital holographic microscopy (DHM) systems, interference patterns are captured by a photo-sensitive array detector located at the image plane of an input object. The object information in these patterns is localized and thus extremely sensitive to phase errors caused by nonlinear hologram recordings (grating profiles are either square or saturated sinusoidal) or inadequate sampling regarding the information coverage (undersampled around the Nyquist frequency or arbitrarily oversampled). Here, we propose a solution for both hologram recording problems through implementing a photon-counting detector (PCD) mounted on a motorized XY translation stage. In such a way, inherently linear (because of a wide dynamic range of PCD) and optimum sampled (due to adjustable steps) digital holograms in the image plane configuration are recorded. Optimum sampling is estimated based on numerical analysis. The validity of the proposed approach is confirmed experimentally.

Morphology and statistics of wide-spectrum speckles

Although the theory of scattered speckles was initially established via idealization of treating the incident light as monochromatic, phenomenon and regulations of wide-spectrum speckles are yet urgent to be studied, with immense growing applications of broadband source such as femtosecond laser, light-emitting-diode and sunlight illumination. Here we quantitatively analyze the morphology and statistics of speckles produced by a point-like source with wide-spectrum, using a phase plate model to describe the scattering layer. Due to differences in induced phase related to wavelength, wide-spectrum speckle patterns appear radial divergence in intensity distribution, as well as in visibility of both speckles and that of the second-order coherence. This is significantly different from the translation-invariance of monochromatic speckles. The spatially-varying morphology and statistics of the speckles contain spatial and spectral information of the incidence, thus can be used as an indicator to achieve optical metrology or sensing with a wide-spectrum source in the scattering environment.

Recording point spread functions by wavefront modulation for interferenceless coded aperture correlation holography

Coded aperture correlation holography (COACH) needs the point spread function (PSF) for image reconstruction. Utilizing a pinhole to generate a point light source is the most frequently adopted method for measuring PSF, which, however, has significant issues to resolve. One of the problems is that the resolution of the reconstructed result is limited by the cutoff frequency of the pinhole. The other is that the far-field PSF is undetectable because the amount of light illuminance decreases with the distance. In this work, we present a method for recording the PSF based on wavefront modulation. By modulating a plane wave with both the carrier spherical wave and the coded phase mask, we obtain a virtual point spread function (VPSF) that is used for image reconstruction. It is shown that the resolution of reconstructed results is not limited by the pinhole. We experimentally demonstrate high-resolution reconstruction by the VPSF.

Correlative all-optical quantification of mass density and mechanics of subcellular compartments with fluorescence specificity

Quantitative measurements of physical parameters become increasingly important for understanding biological processes. Brillouin microscopy (BM) has recently emerged as one technique providing the 3D distribution of viscoelastic properties inside biological samples - so far relying on the implicit assumption that refractive index (RI) and density can be neglected. Here, we present a novel method (FOB microscopy) combining BM with optical diffraction tomography and epifluorescence imaging for explicitly measuring the Brillouin shift, RI, and absolute density with specificity to fluorescently labeled structures. We show that neglecting the RI and density might lead to erroneous conclusions. Investigating the nucleoplasm of wild-type HeLa cells, we find that it has lower density but higher longitudinal modulus than the cytoplasm. Thus, the longitudinal modulus is not merely sensitive to the water content of the sample - a postulate vividly discussed in the field. We demonstrate the further utility of FOB on various biological systems including adipocytes and intracellular membraneless compartments. FOB microscopy can provide unexpected scientific discoveries and shed quantitative light on processes such as phase separation and transition inside living cells.

Maskless Fourier transform holography

Fourier transform holography is a lensless imaging technique that retrieves an object's exit-wave function with high fidelity. It has been used to study nanoscale phenomena and spatio-temporal dynamics in solids, with sensitivity to the phase component of electronic and magnetic textures. However, the method requires an invasive and labor-intensive nanopatterning of a holography mask directly onto the sample, which can alter the sample properties, forces a fixed field-of-view, and leads to a low signal-to-noise ratio at high resolution. In this work, we propose using wavefront-shaping diffractive optics to create a structured probe with full control of its phase at the sample plane, circumventing the need for a mask. We demonstrate in silico that the method can image nanostructures and magnetic textures and validate our approach with a visible light-based experiment. The method enables investigation of a plethora of phenomena at the nanoscale including magnetic and electronic phase coexistence in solids, with further uses in soft and biological matter research.

Roadmap on Digital Holography-Based Quantitative Phase Imaging

Quantitative Phase Imaging (QPI) provides unique means for the imaging of biological or technical microstructures, merging beneficial features identified with microscopy, interferometry, holography, and numerical computations. This roadmap article reviews several digital holography-based QPI approaches developed by prominent research groups. It also briefly discusses the present and future perspectives of 2D and 3D QPI research based on digital holographic microscopy, holographic tomography, and their applications.

Biospeckle Analysis and Biofilm Electrostatic Tests, Two Useful Methods in Microbiology

The development of more sensitive methodologies, capable of quickly detecting and monitoring a microbial population present in a specific biological matrix, as well as performing to allow for the study of all its metabolic changes (e.g., during the formation of biofilm) to occur, is an essential requirement for both well-being and the food industry. Two techniques, in particular, have gained the attention of scientists: The first is “biospeckle”, an optical technique representing an innovative tool for applications in food quality, food safety, and nutraceuticals. With this technique, we can quickly evaluate and monitor the presence of bacteria (or their proliferation) in a solid or liquid biological matrix. In addition, the technique is helpful in quantifying and optimizing the correct storage time of the pro-biotics, if they are entrapped in matrices such as alginate and follow their survival rate in simulated gastro-intestinal conditions. A second technique with great chances is the “biofilm electrostatic test” (BET). BET undoubtedly represents a fast, simple, and highly reproducible tool suitable for admitting the evaluation of the in vitro bacterial capacity in order to adhere through an electrostatic interaction with a pyro-electrified carrier after only 2 h of incubation. BET could represent the way for a quick and standardized evaluation of bacterial resistance among biofilm-producing microorganisms through a fast evaluation of the potential presence of the biofilm.

Speckle-free holography with partially coherent light sources and camera-in-the-loop calibration

Computer-generated holography (CGH) holds transformative potential for a wide range of applications, including direct-view, virtual and augmented reality, and automotive display systems. While research on holographic displays has recently made impressive progress, image quality and eye safety of holographic displays are fundamentally limited by the speckle introduced by coherent light sources. Here, we develop an approach to CGH using partially coherent sources. For this purpose, we devise a wave propagation model for partially coherent light that is demonstrated in conjunction with a camera-in-the-loop calibration strategy. We evaluate this algorithm using light-emitting diodes (LEDs) and superluminescent LEDs (SLEDs) and demonstrate improved speckle characteristics of the resulting holograms compared with coherent lasers. SLEDs in particular are demonstrated to be promising light sources for holographic display applications, because of their potential to generate sharp and high-contrast two-dimensional (2D) and 3D images that are bright, eye safe, and almost free of speckle.

Gaze-Contingent Retinal Speckle Suppression for Perceptually-Matched Foveated Holographic Displays

Computer-generated holographic (CGH) displays show great potential and are emerging as the next-generation displays for augmented and virtual reality, and automotive heads-up displays. One of the critical problems harming the wide adoption of such displays is the presence of speckle noise inherent to holography, that compromises its quality by introducing perceptible artifacts. Although speckle noise suppression has been an active research area, the previous works have not considered the perceptual characteristics of the Human Visual System (HVS), which receives the final displayed imagery. However, it is well studied that the sensitivity of the HVS is not uniform across the visual field, which has led to gaze-contingent rendering schemes for maximizing the perceptual quality in various computer-generated imagery. Inspired by this, we present the first method that reduces the "perceived speckle noise" by integrating foveal and peripheral vision characteristics of the HVS, along with the retinal point spread function, into the phase hologram computation. Specifically, we introduce the anatomical and statistical retinal receptor distribution into our computational hologram optimization, which places a higher priority on reducing the perceived foveal speckle noise while being adaptable to any individual's optical aberration on the retina. Our method demonstrates superior perceptual quality on our emulated holographic display. Our evaluations with objective measurements and subjective studies demonstrate a significant reduction of the human perceived noise.

Artifact-free holographic light shaping through moving acousto-optic holograms

Holographic light modulation is the most efficient method to shape laser light into well-defined patterns and is therefore the means of choice for many intensity demanding applications. During the last two decades, spatial light modulators based on liquid crystals prevailed among several technologies and became the standard tool to shape light holographically. But in the near future, this status might be challenged by acousto-optic deflectors. These devices are well known for their excelling modulation rates and high optical power resilience. But only few scattered precedents exist that demonstrate their holographic capabilities, despite the many interesting properties that they provide. We implemented a holographic acousto-optic light modulation (HALM) system, that is based on displaying holograms on acousto-optic deflectors. We found that this system can eliminate the ubiquitous coherent artifacts that arise in holography through the inherent motion of acousto-optic holograms. That distinguishes our approach from any other holographic modulation technique and allows to reconstruct intensity patterns of the highest fidelity. A mathematical description of this effect is presented and experimentally confirmed by reconstructing images holographically with unprecedented quality. Our results suggest that HALM promotes acousto-optic deflectors from highly specialized devices to full-fledged spatial light modulators, that can compete in a multitude of applications with LC-SLMs. Especially applications that require large optical output powers, high modulation speeds or accurate gray-scale intensity patterns will profit from this technology. We foresee that HALM may play a major role in future laser projectors and displays, structured illumination microscopy, laser material processing and optical trapping.