Pure Phase Objects Research Articles

Spin–orbit optical broadband achromatic spatial differentiation imaging

Spatial optical analog differentiation allows ultrahigh-speed and low-power-consumption of image processing, as well as label-free imaging of transparent biological objects. Optical analog differentiation with broadband and incoherent sources is appealing for its multi-channels and multi-task information processing, as well as the high-quality differentiation imaging. Currently, broadband and incoherent optical differentiation is still challenging. Here, a compact and broadband achromatic optical spatial differentiator is demonstrated based on the intrinsic spin–orbit coupling in a natural thin crystal. By inserting a uniaxial crystal just before the camera of a conventional microscope, the spin to orbit conversion will embed an optical vortex to the image field and make a second-order topological spatial differentiation to the field, thus an isotropic differential image will be captured by the camera. The wavelength-independent property of the intrinsic spin–orbit coupling effect allows us to achieve broadband analog computing and achromatic spatial differentiation imaging. With this differentiation imaging method, both amplitude and pure phase objects are detected with high contrast. Transparent living cells and biological tissues are imaged with their edge contours and intracellular details protruded in the edge detection mode and edge enhancement mode, respectively. These findings pave the way for optical analog computing with broadband incoherent light sources and concurrently drive the advancement of high-performance and cost-effective phase contrast imaging.

Polytypic metal chalcogenide nanocrystals.

By engineering chemically identical but structurally distinct materials into intricate and sophisticated polytypic nanostructures, which often surpass their pure phase objects and even produce novel physical and chemical properties, exciting applications in the fields of photovoltaics, electronics and photocatalysis can be achieved. In recent decades, various methods have been developed for synthesizing a library of polytypic nanocrystals encompassing IV, III-V and II-VI polytypic semiconductors. The exceptional performances of polytypic metal chalcogenide nanocrystals have been observed, making them highly promising candidates for applications in photonics and electronics. However, achieving high-precision control over the morphology, composition, crystal structure, size, homojunctions, and periodicity of polytypic metal chalcogenide nanostructures remains a significant synthetic challenge. This review article offers a comprehensive overview of recent progress in the synthesis and control of polytypic metal chalcogenide nanocrystals using colloidal synthetic strategies. Starting from a concise introduction on the crystal structures of metal chalcogenides, the subsequent discussion delves into the colloidal synthesis of polytypic metal chalcogenide nanocrystals, followed by an in-depth exploration of the key factors governing polytypic structure construction. Subsequently, we provide comprehensive insights into the physical properties of polytypic metal chalcogenide nanocrystals, which exhibit strong correlations with their applications. Thereafter, we emphasize the significance of polytypic nanostructures in various applications, such as photovoltaics, photocatalysis, transistors, thermoelectrics, stress sensors, and the electrocatalytic hydrogen evolution. Finally, we present a summary of the recent advancements in this research field and provide insightful perspectives on the forthcoming challenges, opportunities, and future research directions.

Surface topography detection based on an optical differential metasurface.

Surface topography detection can extract critical characteristics from objects, playing an important role in target identification and precision measurement. Here, an optical method with the advantages of low power consumption, high speed, and simple devices is proposed to realize the surface topography detection of low-contrast phase objects. By constructing reflected light paths, a metasurface can perform spatial differential operation via receiving the light directly reflected from a target. Therefore, our scheme is experimentally demonstrated as having remarkable universality, which can be used not only for opaque objects, but also for transparent pure phase objects. It provides a new, to the best of our knowledge, application for optical differential metasurfaces in precise detection of microscale surface topography.

Asymmetric metasurface photodetectors for single-shot quantitative phase imaging

Abstract The visualization of pure phase objects by wavefront sensing has important applications ranging from surface profiling to biomedical microscopy, and generally requires bulky and complicated setups involving optical spatial filtering, interferometry, or structured illumination. Here we introduce a new type of image sensors that are uniquely sensitive to the local direction of light propagation, based on standard photodetectors coated with a specially designed plasmonic metasurface that creates an asymmetric dependence of responsivity on angle of incidence around the surface normal. The metasurface design, fabrication, and angle-sensitive operation are demonstrated using a simple photoconductive detector platform. The measurement results, combined with computational imaging calculations, are then used to show that a standard camera or microscope based on these metasurface pixels can directly visualize phase objects without any additional optical elements, with state-of-the-art minimum detectable phase contrasts below 10 mrad. Furthermore, the combination of sensors with equal and opposite angular response on the same pixel array can be used to perform quantitative phase imaging in a single shot, with a customized reconstruction algorithm which is also developed in this work. By virtue of its system miniaturization and measurement simplicity, the phase imaging approach enabled by these devices is particularly significant for applications involving space-constrained and portable setups (such as point-of-care imaging and endoscopy) and measurements involving freely moving objects.

Quantum enhanced non-interferometric quantitative phase imaging

Quantum entanglement and squeezing have significantly improved phase estimation and imaging in interferometric settings beyond the classical limits. However, for a wide class of non-interferometric phase imaging/retrieval methods vastly used in the classical domain, e.g., ptychography and diffractive imaging, a demonstration of quantum advantage is still missing. Here, we fill this gap by exploiting entanglement to enhance imaging of a pure phase object in a non-interferometric setting, only measuring the phase effect on the free-propagating field. This method, based on the so-called “transport of intensity equation", is quantitative since it provides the absolute value of the phase without prior knowledge of the object and operates in wide-field mode, so it does not need time-consuming raster scanning. Moreover, it does not require spatial and temporal coherence of the incident light. Besides a general improvement of the image quality at a fixed number of photons irradiated through the object, resulting in better discrimination of small details, we demonstrate a clear reduction of the uncertainty in the quantitative phase estimation. Although we provide an experimental demonstration of a specific scheme in the visible spectrum, this research also paves the way for applications at different wavelengths, e.g., X-ray imaging, where reducing the photon dose is of utmost importance.

Sub-Rayleigh dark-field imaging via speckle illumination.

We demonstrate sub-Rayleigh dark-field imaging via speckle illumination. Imaging is achieved with second-order autocorrelated measurement by illuminating objects with hollow conical pseudothermal light. Our scheme can work well for highly transparent amplitude objects, pure phase objects, and even more complex transparent objects. The autocorrelated dark-field images show better resolution than intensity-averaged images and an ability in filtering out low-frequency noises.

Brewster differential microscopy

Imaging of transparent samples such as cells is important in the biomedicine field; however, insignificant absorption and weakly scattering limit the imaging contrast of phase objects. Here, we propose and demonstrate Brewster differential microscopy based on simple optical reflection at the glass interface. The combination of spin–orbit interaction of light and the Brewster effect can perform two-dimensional differentiation to the incident light distribution and, thus, achieves isotropic edge-enhanced imaging of pure phase objects, which overcomes the limitation of traditional one-dimensional imaging. Furthermore, by introducing bias retardation, we also reconstruct the original phase distribution. The proposed microscopic imaging mechanism does not involve any complex modulation devices and takes advantages of simple and low-cost structure. The results indicate that our research shows promising applications for nondestructive imaging of biological cells.

Intrinsic Optical Spatial Differentiation Enabled Quantum Dark-Field Microscopy.

By solving the Maxwell's equations in Fourier space, we find that the cross-polarized component of the dipole scattering field can be written as the second-order spatial differentiation of the copolarized component. This differential operation can be regarded as intrinsic which naturally arises as consequence of the transversality of electromagnetic fields. By introducing the intrinsic spatial differentiation into heralded single-photon microscopy imaging technique, it makes the structure of pure-phase object clearly visible at low photon level, avoiding any biophysical damages to living cells. Based on the polarization entanglement, the switch between dark-field imaging and bright-field imaging is remotely controlled in the heralding arm. This research enriches both fields of optical analog computing and quantum microscopy, opening a promising route toward a nondestructive imaging of living biological systems.

Experimental optical encryption based on random mask encoding and deep learning

We present an experimental scheme for optical encryption using random mask encoding and deep learning technique. A phase image is encrypted into a speckle pattern by a random amplitude modulation in the optical transmission. Before decryption processing, a neural network model is used to learn the mapping relationship between the pure-phase object and the speckle image rather than characterizing the filter film used in the scheme explicitly or parametrically. The random binary mask is made by a polyethylene terephthalate film and 2500 object-speckle pairs are used for training. The experimental results demonstrate that the proposed scheme based on deep learning could be successfully used as a random binary mask encrypted image processor, which can quickly output the primary image with high quality from the cyphertext.

Quantitative pure-phase object reconstruction under single-shot Fourier measurement via deep learning

The phase retrieval problem, usually known as reconstructing an estimate of phase object from its diffraction intensity patterns, exists widely in the optical imaging field. In this paper, a deep convolutional neural network (CNN) framework is developed to accomplish the phase reconstruction given a single-shot Fourier measurement, without the requirement of prior knowledge (like nonnegativity and support constraints) or time-consuming iterations. A receptive field and input enhance learning-based design principle is applied to establish the neural network architecture. And a new loss function that combines the structural similarity (SSIM) index and the mean square error (MSE) is taken to further improve the network training. Quantitative (the average SSIM and relative MSE are ~ 0.9900 and 0.0012, respectively) and qualitative (SSIM, ranging from 0.87 to 0.95) phase reconstructions are achieved in the numerical simulation and experiment, respectively. Once the proposed network is well trained, it is convenient for the users to perform the phase reconstruction at a remarkably fast speed (~ 0.425 s). Moreover, our network is considerably robust to different noises and could be trained to additionally function as a denoiser in the phase retrieval process. In practice, the proposed method is able to build an accurate propagation model of the practical imaging system, and significantly enhance and improve the spatial resolution. With the great convenience and high accuracy of phase recovery, the proposed deep CNN framework may be helpful to solve the phase retrieval problem in Fourier imaging systems, like coherent diffraction imaging (CDI), X-ray imaging, and imaging through diffusers, etc.

Complexity-guided Fourier phase retrieval from noisy data

Reconstruction of a stable and good quality solution from noisy single-shot Fourier intensity data is a challenging problem for phase retrieval algorithms. We examine behavior of the solution provided by the hybrid input-output (HIO) algorithm for noisy data, from the perspective of the complexity guidance methodology that was introduced by us in an earlier paper [J. Opt. Soc. Am. A36, 202 (2019)JOAOD60740-323210.1364/JOSAA.36.000202]. We find that for noisy data, the complexity of the solution outside the support keeps increasing as the HIO iterations progress. Based on this observation, a strategy for controlling the solution complexity within and outside the support during the HIO iterations is proposed and tested. In particular, we actively track and control the growth of complexity of the solution outside the support region with iterations. This in turn provides us with guidance regarding the level to which the complexity of the solution within the support region needs to be adjusted, such that the total solution complexity is equal to that estimated from raw Fourier intensity data. In our studies, Poisson noise with mean photon counts per pixel in the Fourier intensity data ranges over four orders of magnitude. We observe that the performance of the proposed strategy is noise robust in the sense that with increasing noise, the quality of the phase solution degrades gradually. For higher noise levels, the solution loses textural details while retaining the main object features. Our numerical experiments show that the proposed strategy can uniformly handle pure phase objects, mixed amplitude-phase objects, and the case of dc blocked Fourier intensity data. The results may find a number of applications where single-shot Fourier phase retrieval is critical to the success of corresponding applications.

The effect of noise, a constant background, and bit depth on the phase retrieval of pure phase objects

In the current study, we investigate the effect of uniform white noise, Poisson noise and a constant background on the phase retrieval of pure phase objects. We also study the influence of the aforementioned factors on phase retrieval at different bit depths of intensity measurements. An algorithm called PhaseLift is used for phase retrieval as it requires a small number of modulating masks and can retrieve the phase of an object from sparse intensity measurements of low bit depth. A test object is modulated by eight random masks generated from a single mask and the phase of the object is retrieved from coded diffraction patterns. Different levels of uniform white noise, Poisson noise and constant background are superimposed on the diffraction patterns and the root-mean-square error (RMSE) of the retrieved object is calculated at each level. The results suggest that Poisson noise and a constant background at the same level cause similar RMSE compared to uniform white noise. Lowering the bit depth from 18-bits to 14-bits resulted in the decrease of the RMSE caused by Poisson noise and a constant background. We conclude that the effects of noise and constant background can be reduced by lowering the bit depth.

Ghost diffraction holographic microscopy

Unconventional systems that adopt the concept of ghost schemes have led to advancements in some imaging applications. However, their application in quantitative phase imaging remains a challenge. Here, we introduce a basis for quantitative phase imaging with ghost diffraction and demonstrate ghost diffraction holographic microscopy for complex-valued imaging. We achieve this by introducing an off-axis holography approach in the modified ghost diffraction system. We also realize a correlation hologram in the cross-correlation of intensities from two detectors in the modified ghost diffraction setup and digitally process the correlation hologram to image complex-valued objects. To generate experiment results, we use a modified interferometer setup and exploit the spatial statistics of the scattered field from a time-frozen pseudothermal light source. Finally, we evaluate the efficacy of the approach by simulation and follow that with experiments that demonstrate imaging of pure phase objects, planar transparencies, and resolution test targets, among others.

Dark-field ghost imaging

Ghost imaging is a promising technique for shape reconstruction using two spatially correlated beams: one beam interacts with a target and is collected with a bucket detector, and the other beam is measured with a pixelated detector. However, orthodox ghost imaging always provides unsatisfactory results for unstained samples, phase objects, or highly transparent objects. Here we present a dark-field ghost imaging technique that can work well for these "bad" targets. The only difference from orthodox ghost imaging is that the bucket signals rule out the target's unscattered beam. As experimental proof, we demonstrate images of fine copper wires, quartz fibers, scratched and damaged glass plates, a pure phase object, and biospecimens.

Continuous-wave terahertz quantitative dual-plane ptychography

Terahertz (THz) radiation lies between the millimeter and infrared region of the electromagnetic spectrum, which is typically defined as the frequency range of 0.1–10 THz and the corresponding wavelength ranges from 30 μm to 3 mm. Terahertz radiation due to wide spectrum, high penetration, low energy, and other important features, has been a valuable tool for imaging and non-destructive testing on a submillimeter scale. Continuous-wave (CW) terahertz ptychography is a type of phase-contrast technique with advantages of simple set-up and large field-of-view. It retrieves the complex-valued transmission function of the specimen and the probe function at the same time. The extended ptychographic iterative engine (ePIE) algorithm is used as the reconstruction algorithm in the field of ptychography, because it is relatively simple, and can use computer memory efficiently. However, the problem of algorithm convergence delay makes us unable to acquire the reconstruction result very quickly. Since the ptychography is a problem of retrieving phase information, physical constraints affect the convergence speed of the algorithm strongly. In this paper, we propose a dual-plane ePIE (dp-ePIE) algorithm for CW THz ptychography. By moving detector along the axis and capturing diffraction patterns of one zone of an object at two recording planes, then, two sets of patterns used as the constraints simultaneously can increase the diversity of experimental parameter. Hence, the convergence rate can be improved. The simulation results suggest better reconstruction fidelity with a faster convergence rate by the dp-ePIE algorithm. The dual-plane terahertz ptychography experimental setup is built based on 2.52 THz optically pumped laser and Pyrocam-III pyroelectric array detector. Compared with other methods to increase the diversity of measurement, the setup of dual-plane ptychography can be compact and simple, thus reducing the terahertz wave transmission loss. A polypropylene sample is adopted and it is approximated as a pure phase object. No-reference structural sharpness (NRSS) is utilized as a quantitative evaluation index. It takes 45.086 s to achieve NRSS value of 0.9831 by using the dp-ePIE algorithm in 10 iterations, while the NRSS value and calculation time for e-PIE algorithm are 0.9531 and 57.117 s (20 loops), respectively. The experimental results show that the dp-ePIE algorithm can obtain high-quality amplitude and phase distribution with less iterations than the traditional ePIE algorithm.

Aberration-insensitive microscopy using optical field-correlation imaging

The possibility to reduce the effect of optical aberrations has been proposed in several publications on classical ghost imaging. The two-armed ghost-imaging systems make use of spatially incoherent illumination and point-by-point scanned intensity-correlation measurements in the arms. In this work, we introduce a novel ghostlike imaging method that uses a Mach-Zehnder interferometer and is based on optical-field interference instead of intensity correlations. The method allows us to obtain sharp images of microscopic objects even in the presence of severe aberrations that completely destroy the intensity-based image. Furthermore, pure phase objects can be imaged with micrometer-scale resolution in the presence of strong aberrations, which has not been demonstrated previously with a correlation-based imaging technique. In the setup, we use a light-emitting diode source and an ordinary camera as the only light detector. The imaging approach that we put forward in this work may find significant applications in advanced optical microscopy, optical coherence tomography, and a variety of interferometric sensors and detectors.

Orientation-selective edge enhancement of phase objects

Abstract We present a method for the orientation-selective enhancement of the first derivatives − i.e. the edges − of a pure phase object. The proposed method is based on the transport-of-intensity equation (TIE). The TIE contains a term proportional to the scalar product of the phase gradient and an intensity gradient, which plays the role of amplifying factor of the first derivatives. We will show that if the intensity gradient is implemented in the optical setup as a moving amplitude mask with a relatively sharp border − or eventually, a digital shifting mask displayed in a liquid crystal display − it is possible to generate a synthetic image of the phase object with enhanced edges. The proposed technique is potentially useful in biological and biomedical research. Validation experiments and preliminary qualitative results illustrating the generation of synthetic images with enhanced edges are presented.

Optical image processing with metasurface dark modes.

Here we consider image processing using the optical modes of metasurfaces with an angle-dependent excitation. These spatially dispersive modes can be used to directly manipulate the spatial frequency content of an incident field, suggesting their use as ultra-compact alternatives for analog optical information processing. A general framework for describing the filtering process in terms of the optical transfer functions is provided. In the case where the relevant mode cannot be excited with a normally incident plane wave (a dark mode), high-pass filtering is obtained. We provide examples demonstrating filtering of both amplitude and pure phase objects.

Single-Shot X-ray Phase Retrieval through Hierarchical Data Analysis and a Multi-Aperture Analyser

A multi-aperture analyser set-up was recently developed for X-ray phase contrast imaging and tomography, simultaneously attaining a high sensitivity and wide dynamic range. We present a single-shot image retrieval algorithm in which differential phase and dark-field images are extracted from a single intensity projection. Scanning of the object is required to build a two-dimensional image, because only one pre-sample aperture is used in the experiment reported here. A pure-phase object approximation and a hierarchical approach to the data analysis are used in order to overcome numerical instabilities. The single-shot capability reduces the exposure times by a factor of five with respect to the standard implementation and significantly simplifies the acquisition procedure by only requiring sample scanning during data collection.

An improved ring removal procedure for in-line x-ray phase contrast tomography

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.