Digital Holographic Imaging Research Articles

Near-Infrared Self-Powered Linearly Polarized Photodetection and Digital Incoherent Holography Using WSe2/ReSe2 van der Waals Heterostructure.

Polarization-sensitive photodetection has attracted considerable attention as an emerging technology for future optoelectronic applications such as three-dimensional (3D) imaging, quantum optics, and encryption. However, traditional photodetectors based on Si or III-V InGaAs semiconductors cannot directly detect polarized light without additional optical components. Herein, we demonstrate a self-powered linear-polarization-sensitive near-infrared (NIR) photodetector using a two-dimensional WSe2/ReSe2 van der Waals heterostructure. The WSe2/ReSe2 heterojunction photodiode with semivertical geometry exhibits excellent performance: an ideality factor of 1.67, a broad spectral photoresponse of 405-980 nm with a significant photovoltaic effect, outstanding linearity with a linear dynamic range wider than 100 dB, and rapid photoswitching behavior with a cutoff frequency up to 100 kHz. Strongly polarized excitonic transitions around the band edge in ReSe2 lead to significant 980 nm NIR linear-polarization-dependent photocurrent. This linear polarization sensitivity remains stable even after exposure to air for longer than five months. Furthermore, by leveraging the NIR (980 nm)-selective linear polarization detection of this photodiode under photovoltaic operation, we demonstrate digital incoherent holographic 3D imaging.

Improving particle detection and size estimation accuracy in digital in-line holography using autoregressive interpolation.

The accuracy of particle detection and size estimation is limited by the physical size of the digital sensor used to record the hologram in a digital in-line holographic imaging system. In this paper, we propose to utilize the autoregressive (AR) interpolation of the hologram to increase pixel density and, effectively, the quality of hologram reconstruction. Simulation studies are conducted to evaluate the influence of AR interpolation of a hologram on the accuracy of detection and size estimation of single and multiple particles of varying sizes. A comparative study on the performance of different interpolation techniques indicates the advantage of the proposed AR hologram interpolation approach. An experimental result is provided to validate the suitability of the proposed algorithm in practical applications.

Characterization and mitigation of aerosols and spatters from ultrasonic scalers

BackgroundDental procedures often produce aerosols and spatter, which have the potential to transmit pathogens such as severe acute respiratory syndrome coronavirus 2. The existing literature is limited. MethodsAerosols and spatter were generated from an ultrasonic scaling procedure on a dental manikin and characterized via 2 optical imaging methods: digital inline holography and laser sheet imaging. Capture efficiencies of various aerosol mitigation devices were evaluated and compared. ResultsThe ultrasonic scaling procedure generated a wide size range of aerosols (up to a few hundred μm) and occasional large spatter, which emit at low velocity (mostly < 3 m/s). Use of a saliva ejector and high-volume evacuator (HVE) resulted in overall reductions of 63% and 88%, respectively, whereas an extraoral local extractor (ELE) resulted in a reduction of 96% at the nominal design flow setting. ConclusionsThe study results showed that the use of ELE or HVE significantly reduced aerosol and spatter emission. The use of HVE generally requires an additional person to assist a dental hygienist, whereas an ELE can be operated hands free when a dental hygienist is performing ultrasonic scaling and other operations. Practical ImplicationsAn ELE aids in the reduction of aerosols and spatters during ultrasonic scaling procedures, potentially reducing transmission of oral or respiratory pathogens like severe acute respiratory syndrome coronavirus 2. Position and airflow of the device are important to effective aerosol mitigation.

Fast and accurate autofocusing algorithm in digital holography based on particle swarm optimization

Numerical autofocusing is one of the key features of digital holographic imaging modality. The conventional procedure of hologram reconstruction at different reconstruction distances followed by the focal plane detection based on a specific image quality metric is usually time consuming. We propose a fast and accurate autofocusing algorithm based on particle swarm optimization technique. Instead of reconstructing hologram at a large number of equidistant positions within the measurement volume, reconstructions are performed at a few random positions, considered as particles, which are updated in an iterative manner. This approach results in significant improvement in the accuracy and computational efficiency of the autofocusing procedure. Simulation and experimental results are provided to demonstrate the applicability of the proposed method.

Classification of unlabeled cells using lensless digital holographic images and deep neural networks.

Image-based cell analytic methodologies offer a relatively simple and economical way to analyze and understand cell heterogeneities and developments. Owing to developments in high-resolution image sensors and high-performance computation processors, the emerging lensless digital holography technique enables a simple and cost-effective approach to obtain label-free cell images with a large field of view and microscopic spatial resolution. The holograms of three types of cells, including MCF-10A, EC-109, and MDA-MB-231 cells, were recorded using a lensless digital holography system composed of a laser diode, a sample stage, an image sensor, and a laptop computer. The amplitude images were reconstructed using the angular spectrum method, and the sample to sensor distance was determined using the autofocusing criteria based on the sparsity of image edges and corner points. Four convolutional neural networks (CNNs) were used to classify the cell types based on the recovered holographic images. Classification of two cell types and three cell types achieved an accuracy of higher than 91% by all the networks used. The ResNet and the DenseNet models had similar classification accuracy of 95% or greater, outperforming the GoogLeNet and the CNN-5 models. These experiments demonstrated that the CNNs were effective at classifying two or three types of tumor cells. The lensless holography combined with machine learning holds great promise in the application of stainless cell imaging and classification, such as in cancer diagnosis and cancer biology research, where distinguishing normal cells from cancer cells and recognizing different cancer cell types will be greatly beneficial.

Generalized optimization framework for pixel super-resolution imaging in digital holography.

The imaging quality of in-line digital holography is challenged by the twin-image and aliasing effects because sensors only respond to intensity and pixels are of finite size. As a result, phase retrieval and pixel super-resolution techniques serve as two essential ingredients for high-fidelity and high-resolution holographic imaging. In this work, we combine the two as a unified optimization problem and propose a generalized algorithmic framework for pixel-super-resolved phase retrieval. In particular, we introduce the iterative projection algorithms and gradient descent algorithms for solving this problem. The basic building blocks, namely the projection operator and the Wirtinger gradient, are derived and analyzed. As an example, the Wirtinger gradient descent algorithm for pixel-super-resolved phase retrieval, termed as Wirtinger-PSR, is proposed and compared with the classical error-reduction algorithm. The Wirtinger-PSR algorithm is verified with both simulated and experimental data. The proposed framework generalizes well to various physical settings and helps bridging the gap between empirical studies and theoretical analyses.

Effects of surface roughness on splashing characteristics of large droplets with digital inline holographic imaging

Ice accretion on aircraft wings due to Supercooled Large Droplet (SLD) has a significant impact on flight safety. The dynamic behaviours of large droplet, such as deformation, breakup and splashing, have significant effects on icing accretion. The corresponding studies have been carried out experimentally and numerically, and empirical models to predict the dynamic behaviours of large droplets have been proposed. However, few empirical models involve surface roughness effects, especially its effects on the secondary droplets during icing accretion. In this paper, an experimental investigation on the impact of droplets onto surfaces with different roughness was conducted by using the high-speed Digital Inline Holography (DIH). The rapid splashing processes of droplets with Weber number around 570 and Mundo impact parameter K around 240 were captured and reconstructed based on a wavelet-based algorithm. Results show that DIH is suitable to diagnose the secondary droplets with a wide size range and record their velocities and locations. The roughness of the impact surface has a positive effect on the dynamics of splashing droplets, and the parameters including diameter, velocity, splash angle, splash height and mass-loss rate of splashing droplets rise with the increase of roughness. The new empirical correlations of the splashing characteristics of secondary droplets were fitted and developed, which could be used to update the current icing simulation models to take into account the effect of impact surface roughness on large droplets dynamics. This fundamental study may also be applied to the industrial applications including wind turbine icing, inkjets, sprays, as well as the erosion and formation of ice layers.

Digital holographic polarimeter using dual reference beam interferometry.

An off-axis digital holographic imaging polarimeter was developed to estimate the Jones matrices of an object. The Jones vector image of the electric field returned from the object is determined from a single holographic recording using the interference between the dual, nearly orthogonal, reference beams. The technique compensates for phase variations in the optical beam paths between the recorded holograms and relaxes the need to generate orthogonal illumination polarization states. A minimization algorithm was developed to compute an estimation of the Jones matrix image of an object based on a set of measured Jones vector images. A proof-of-concept demonstration was performed to compute an estimated Jones matrix image of a polarimetrically complex object using digital holograms recorded with 6 different illumination polarizations.

Effect of displacement in object plane on reconstructed image in lens-based digital holography

Optical properties of lenses play significant role in digital holographic setups to increase their applications in several fields of imaging and non-destructive testing. In present work, we investigate the effect of introduction of lenses on quality of reconstructed images when they are placed between the object and the image sensor in digital holography. We define a range of propagation distance suitable for recording digital holograms using different off-axis digital holographic setups. The reconstruction results of conventional off-axis digital holographic setup are taken as reference to compare them with lens-based digital holographic setups. Three different digital holographic setups are realised using lenses i.e. concave lens-based setup, convex lens-based setup, and combined concave and convex lenses-based setup. The quality of the reconstructed image is measured by calculating their structural similarity index measure (SSIM) values. These values compare the reconstructed image obtained in the experiment with a reference image of the object obtained through its computer generated hologram (CGH). Performance of these digital holographic setups is compared on the basis of SSIM values of reconstructed images calculated for different separation between object to sensor. On the basis of SSIM values, a range of distances suitable for recording digital holograms for each setup is obtained as 220 mm to 400 mm for the concave lens-based setup, 560 mm to 800 mm for convex lens-based setup, and 220 mm to 600 mm for the concave-convex lens-based setup using concave lens of 50 mm focal length and a convex lens of 80 mm focal length in the experiments.

Research on incoherent self-reference digital holography imaging system

We proposed an incoherent self-interference digital holography imaging system based on the Michelson interferometer. The proposed system records holograms of USAF1951 resolution target, herbaceous stem crosscut, and osteocyte. The reconstruction of the captured hologram using a three-step generalized phase shift can effectively eliminate bias and a twin image and obtain a clear reconstructed image. Element 3 in group 9 on the USAF1951 resolution target can be clearly seen, and the resolution achieves 645 lp / mm. Results indicate that the diffraction distance can influence the reconstructed image quality, which was confirmed by analyzing their relationship. In addition, the hair hologram was reconstructed, thereby demonstrating that the proposed system can record a 3D image of the object.

Aberration-free digital holographic phase imaging using the derivative-based principal component analysis.

.Significance: Digital holographic microscopy is widely used to get the quantitative phase information of transparent cells.Aim: However, the sample phase is superimposed with aberrations. To quantify the phase information, aberrations need to be fully compensated.Approach: We propose a technique to obtain aberration-free phase imaging, using the derivative-based principal component analysis (dPCA).Results: With dPCA, almost all aberrations can be extracted and compensated without requirements on background segmentation, making it efficient and convenient.Conclusions: It solves the problem that the conventional principal component analysis (PCA) algorithm cannot compensate the common but intricate higher order cross-term aberrations, such as astigmatism and coma. Moreover, the dPCA strategy proposed here is not only suitable for aberration compensation but also applicable for other cases where there exist cross-terms that cannot be analyzed with the PCA algorithm.

Dense-U-net: Dense encoder–decoder network for holographic imaging of 3D particle fields

Digital holographic imaging is able to reconstruct phase and three-dimensional (3D) information of an object from a one-shot two-dimensional (2D) lensless hologram. A dense encoder–decoder network, called Dense-U-net, is proposed to realize the reconstruction of a 3D particle field. The radii and 3D coordinates of the particles are encoded into a 2D grayscale image as the ground truth. The 2D hologram was served as the input of the network. A Dense_Block is designed and added to the encoder and decoder of the traditional U-net model. Each layer takes the inputs from all previous layers and passes its own feature map to all subsequent layers. Thus, as the diffraction is distributed throughout the entire hologram, both the features with high signal-to-noise ratio at the center of the particle and the diffraction features with low signal-to-noise ratio around the particle can be learned, thereby facilitating the full characterization of the particles. Using the specially designed dense connection module, network training can be accomplished with fewer parameters and faster speeds.

Phase shifted-lateral shearing digital holographic microscopy imaging for early diagnosis of cysts in soft tissue-mimicking phantom

The diagnosis of cyst structures that can be seen in almost every part of the body can be made using various medical imaging methods recently. Although the used methods and devices provide convenience in diagnosis and treatment, sometimes they can not detect early-stage cyst structures without showing any symptoms. In this study, the cystic structures with different size and formation in phantoms which are soft tissue-mimicking structures created without the need for any living tissue obtained with biopsy process are visualized by the proposed Phase Shifted-Lateral Shearing Digital Holographic Microscopy in three dimensional. The proposed method is verified with experimental results obtained by using various phantom models created at different times and structures. Experimental results illustrate the applicability of the proposed method for imaging of the cyst structures in the created soft tissue-mimicking phantoms even if they are in different structures, formations and stages (especially in early stage). In other respects, it enables to image the biological specimens in small size using simple and low-cost setup.

Digital Holography and 3D Imaging 2020: introduction to the feature issue.

This feature issue of JOSA A and Applied Optics is dedicated to the fourteenth OSA Topical Meeting "Digital Holography and 3D Imaging" held 22-26 June 2020 in a virtual meeting. The conference, taking place every year, is a focal point for global technical interchange in the field of digital holography and 3D imaging, providing premier opportunities for people working in the field to present their new advances in research and development. Papers presented at the meeting highlight current research in digital holography and three-dimensional imaging, including interferometry, phase microscopy, phase retrieval, novel holographic processes, 3D and novel holographic displays, integral imaging, computer-generated holograms, compressive holography, 3D holographic display, AR display, full-field tomography, specific image and signal processing, and holography with various light sources, including coherent to incoherent and x-ray to terahertz waves. Techniques of digital holography and of 3D imaging have numerous applications, such as the state-of-the-art technological developments that are currently underway and stimulate further novel applications of digital holography and 3D imaging in biomedicine, deep learning, and scientific and industrial metrologies.

Digital Holography and 3D Imaging 2020: introduction to the feature issue.

This feature issue of JOSA A and Applied Optics is dedicated to the fourteenth OSA Topical Meeting "Digital Holography and 3D Imaging" held 22-26 June 2020 in a virtual meeting. The conference, taking place every year, is a focal point for global technical interchange in the field of digital holography and 3D imaging, providing premier opportunities for people working in the field to present their new advances in research and development. Papers presented at the meeting highlight current research in digital holography and three-dimensional imaging, including interferometry, phase microscopy, phase retrieval, novel holographic processes, 3D and novel holographic displays, integral imaging, computer-generated holograms, compressive holography, 3D holographic display, AR display, full-field tomography, specific image and signal processing, and holography with various light sources, including coherent to incoherent and x-ray to terahertz waves. Techniques of digital holography and of 3D imaging have numerous applications, such as the state-of-the-art technological developments that are currently underway and have also stimulated further novel applications of digital holography and 3D imaging in biomedicine, deep learning, and scientific and industrial metrologies.

Aperture synthesis based solely on phase images in digital holography

Aperture synthesis is an important approach to improve the lateral resolution of digital holography (DH) techniques. The limitation of the accuracy of registration positions between sub-holograms affects the quality of the synthesized image and even causes the failure of aperture synthesis. It is a major issue in aperture synthesis of DH. Currently intensity images are utilized to find the registration positions of sub-holograms in aperture synthesis. To improve the accuracy of registration positions, we proposed a method based on similarity calculations of the phase images between sub-holograms instead of intensity images. Furthermore, a quantitative indicator, degree of image distortion, was applied to evaluate the synthetic results. Experiments are performed and the results verify that the proposed phase-image-based method is better than the state-of-the-art intensity-image-based techniques in the estimation of registration positions and provides a better synthesized final three-dimensional shape image.

Telecentric in-line-and-off-axis hybrid digital holographic high-resolution reconstruction method

In-line digital holography usually employs a phase retrieval algorithm to decouple the phase information but fails to eliminate the unwanted DC and twin image terms when the measured sample does not agree with the sparsity. While the off-axis digital holography can efficiently remove the unwanted image terms but can not reserve the high frequencies of the sample to realize high resolution. The in-line-and-off-axis hybrid digital holography was then developed to provide a relatively high resolution digital holographic imaging without considering the effect of the unwanted terms. In other words, the in-line-and-off-axis hybrid digital holography merges all of the best virtues of the mentioned-above methods in an efficient and elegant way. However, this state-of-the-art method requires prior knowledge about the diffraction distance, which results in time-consuming and low accuracy. In other sense, telecentric technology can realize non-diffractive imaging without the knowledge about the diffraction distance or spherical aberration or defocusing aberration. Therefore, in this paper, a novel in-line-and-off-axis hybrid digital holography is proposed by introducing telecentric imaging architecture, and the corresponding reconstruction method is further proposed by utilizing constrained iterative approach. In this method, telecentric in-line-and-off-axis hybrid digital holography is first used to acquire focused off-axis and in-line holograms, respectively. The low resolution phase information is reconstructed from the off-axis hologram by using Fourier transform method with the help of the sample-free off-axis hologram, and then multiplexed with the amplitude information obtained from the in-line hologram to act as the initial complex amplitude in the iterative recovery process. As a result, constrained iterations are carried out in the spatial domain and frequency domain to realize high resolution and high speed reconstruction. After simulations, we build an experimental setup and demonstrate the operation of the method with USAF resolution target, onion cells and bee wings. Both the simulation and experimental results show that the proposed method can require no prior knowledge to suppress the phase disturbance caused by the unwanted image terms and optical aberrations, resulting in high speed and full utilization of spatial bandwidth product of the digital camera to yield high resolution reconstruction. We hope that the proposed method will have most practical applications in the case where large resolution, high speed and good quality are needed.

High-Resolution Sampling of a Broad Marine Life Size Spectrum Reveals Differing Size- and Composition-Based Associations With Physical Oceanographic Structure

Observing multiple size classes of organisms, along with oceanographic properties and water mass origins, can improve our understanding of the drivers of aggregations, yet acquiring these measurements remains a fundamental challenge in biological oceanography. By deploying multiple biological sampling systems, from conventional bottle and net sampling to in situ imaging and acoustics, we describe the spatial patterns of different size classes of marine organisms (several microns to ∼10 cm) in relation to local and regional (m to km) physical oceanographic conditions on the Delaware continental shelf. The imaging and acoustic systems deployed included (in ascending order of target organism size) an imaging flow cytometer (CytoSense), a digital holographic imaging system (HOLOCAM), an In Situ Ichthyoplankton Imaging System (ISIIS, 2 cameras with different pixel resolutions), and multi-frequency acoustics (SIMRAD, 18 and 38 kHz). Spatial patterns generated by the different systems showed size-dependent aggregations and differing connections to horizontal and vertical salinity and temperature gradients that would not have been detected with traditional station-based sampling (∼9-km resolution). A direct comparison of the two ISIIS cameras showed composition and spatial patchiness changes that depended on the organism size, morphology, and camera pixel resolution. Large zooplankton near the surface, primarily composed of appendicularians and gelatinous organisms, tended to be more abundant offshore near the shelf break. This region was also associated with high phytoplankton biomass and higher overall organism abundances in the ISIIS, acoustics, and targeted net sampling. In contrast, the inshore region was dominated by hard-bodied zooplankton and had relatively low acoustic backscatter. The nets showed a community dominated by copepods, but they also showed high relative abundances of soft-bodied organisms in the offshore region where these organisms were quantified by the ISIIS. The HOLOCAM detected dense patches of ciliates that were too small to be captured in the nets or ISIIS imagery. This near-simultaneous deployment of different systems enables the description of the spatial patterns of different organism size classes, their spatial relation to potential prey and predators, and their association with specific oceanographic conditions. These datasets can also be used to evaluate the efficacy of sampling techniques, ultimately aiding in the design of efficient, hypothesis-driven sampling programs that incorporate these complementary technologies.

Subsampled digital holographic image reconstruction by a compressive sensing approach.

We show an in-line digital holographic image reconstruction from subsampled holograms with resolution improvement and lensless magnification with high noise immunity by a compressive sensing approach. Our method treats the sensed field as subsampled, low-pass filtered and projected on a Fresnel-Bluestein base in an inverse problem approach to image reconstruction with controlled lensless magnification. So, we have demonstrated by simulation and experimental results that the approach can reconstruct images with quality even when used in holograms obtained from unusual subsampling schemes.

High-fidelity pixel-super-resolved complex field reconstruction via adaptive smoothing.

Pixel super-resolution (PSR) techniques have been developed to overcome the sampling limit in lensless digital holographic imaging. However, the inherent non-convexity of the PSR phase retrieval problem can potentially degrade reconstruction quality by causing the iterations to tend toward a false local minimum. Furthermore, the ill posedness of the up-sampling procedure renders PSR algorithms highly susceptible to noise. In this Letter, we propose a heuristic PSR algorithm with adaptive smoothing (AS-PSR) to achieve high-fidelity reconstruction. By automatically adjusting the intensity constraints on the estimated field, the algorithm can effectively locate the optimal solution and converge with high reconstruction quality, pushing the resolution toward the diffraction limit. The proposed method is verified experimentally within a coherent modulation phase retrieval framework, achieving a twofold improvement in resolution. The AS-PSR algorithm can be further applied to other phase retrieval methods based on alternating projection.