Reflection Imaging Research Articles

Terahertz scanning microscopy with 2λ depth of field based on photonic nanojet generated by a dielectric cuboid probe.

We demonstrate terahertz scanning microscopy using a dielectric cuboid probe (DCP). The protruding part of the DCP is inserted into a waveguide, which is commonly used in the millimeter- and terahertz-wave bands, to generate a photonic jet. The DCP does not require free-space optics, making the system very compact. The DCP generates a 300 GHz beam with full width at half maximum (FWHM) of less than wavelength (λ) in the region from the surface to 2λ ahead. This relatively longer depth of field (DOF) is a great advantage when the imaging target is covered with dielectric material and the probe head cannot be brought close to the imaging target. Also, this eliminates the need for precise feedback control of the distance between the uneven sample and probe, thus simplifying the microscopy system. Taking with this advantage, we demonstrate depth imaging with longitudinal and lateral spatial resolutions of about 10 µm (λ/100) and less than 1 mm (λ), respectively, by using the phase data in a reflective imaging configuration. This technology is expected to aid the realization of an inexpensive and compact high-resolution microscopy system with large DOF in the millimeter- and terahertz-wave regions.

Analysis of grain growth behavior of multicrystalline Mg2Si

Multicrystalline Mg2Si crystal with a diameter of 15 mm was grown via vertical Bridgman method. To clarify the growth mechanism of the multicrystalline structure, the grain growth behavior of the crystal was analyzed. This was carried out through segmenting grains by mean shift clustering using the light intensity profile obtained from multiple optical reflection images of the wafers and stacking the segmented images through the growth direction. Further crystal orientation measurement revealed that a grain with a higher surface energy competitively expanded to the lateral direction during crystal growth. We speculated that the growth behavior occurred because the supercooling was high enough to show difference in each grain’s growth rate. This idea was supported by crystal growth simulation to show a tendency for the crystallization rate to increase toward the latter half growth stage, which is consistent with the assumption for crystal growth with high supercooling.

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

SUMMARY Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source–receiver observation geometry. We develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

Research on adaptive enhancement of robot vision image based on multi-scale filter

ABSTRACT Contrast enhancement and histogram equalisation are two image enhancement methods, which can lead to changes in the edge position of the resulting image, blurring or even loss of details. Therefore, this paper introduces a multi-scale filter to adaptively enhance the robot visual image, improve the brightness of the robot visual image, enrich the image details and reduce the image enhancement time. According to Retinex theory, the characteristic information of robot visual image is obtained, the logarithmic domain operation form of Retinex algorithm is obtained, the robot visual reflection image of high-frequency part is determined, the robot illumination visual image is estimated by multiscale filter, and the scale constant of Gaussian filter is obtained; According to the Retinex algorithm of weighted guided filtering, the robot visual image enhancement process is designed. The experimental results show that the average value of the robot visual image enhanced by this method is 88.63, the standard deviation is 62.78, the information entropy is 8.18, the robot visual image enhancement time is only 5.9s, and the PSNR of the robot visual image is up to 39.92, which proves that the robot visual image enhancement effect of this method is good.

Spectra-separated depth-of-field extended fluorescence imaging through scattering media using speckle deconvolution

Over the last decade, many methods have been proposed to achieve optical imaging through scattering media. Among them, speckle deconvolution utilizing the optical memory effect of the medium is widely employed due to its advantages in imaging speed and relatively simpler setup. However, practical applications of speckle deconvolution method are rarely demonstrated as most of the existing systems are based on transmission geometry to ensure direct incoherent illumination and easy detection. Here we propose an imaging system in reflection configuration that is able to retrieve the hidden fluorescent object behind a thin scattering media by speckle deconvolution. The object speckle pattern and speckle pattern from a point source (point spread function of the system, PSF) are spectrally separated to facilitate non-invasive image acquisitions. It is shown that, to reconstruct object faithfully, spectral de-correlation and chromatic aberration induced depth de-correlation between the object speckle pattern and the PSF have to be compensated. Speckle correlation is employed to characterize the depth-of-field (DOF) range in this reflection imaging system. Within the DOF, focus and defocus effects in the reconstructed objects are observed when rescaling the PSF onto different axial planes. Beyond the DOF, hidden objects that originally fail in reconstruction can be retrieved by PSF stacking and PSF rescaling. The proposed approach is potentially to find wide applications in biomedical imaging, ranging from deep tissue fluorescence microscopy to small animal imaging.

Prediction of severe thunderstorm events with ensemble deep learning and radar data

The problem of nowcasting extreme weather events can be addressed by applying either numerical methods for the solution of dynamic model equations or data-driven artificial intelligence algorithms. Within this latter framework, the most used techniques rely on video prediction deep learning methods which take in input time series of radar reflectivity images to predict the next future sequence of reflectivity images, from which the predicted rainfall quantities are extrapolated. Differently from the previous works, the present paper proposes a deep learning method, exploiting videos of radar reflectivity frames as input and lightning data to realize a warning machine able to sound timely alarms of possible severe thunderstorm events. The problem is recast in a classification one in which the extreme events to be predicted are characterized by a an high level of precipitation and lightning density. From a technical viewpoint, the computational core of this approach is an ensemble learning method based on the recently introduced value-weighted skill scores for both transforming the probabilistic outcomes of the neural network into binary predictions and assessing the forecasting performance. Such value-weighted skill scores are particularly suitable for binary predictions performed over time since they take into account the time evolution of events and predictions paying attention to the value of the prediction for the forecaster. The result of this study is a warning machine validated against weather radar data recorded in the Liguria region, in Italy.

In Situ Process Monitoring and Multichannel Imaging for Vacuum‐Assisted Growth Control of Inkjet‐Printed and Blade‐Coated Perovskite Thin‐Films

AbstractVacuum‐assisted growth (VAG) control is one of the most promising methods for controlling nucleation and crystallization of printed and coated large area lead halide perovskite‐based layers for optoelectronics. To coat or print homogeneous high‐quality perovskite thin‐films at high fabrication yield, real‐time process monitoring of the VAG is pivotal. In response, a 2.1‐megapixel multichannel photoluminescence (PL) and reflection imaging system is developed and employed for the simultaneous spatial in situ analysis of drying, nucleation, and crystal growth during VAG and subsequent thermal annealing of inkjet‐printed and blade‐coated perovskite thin‐films. It is shown that the VAG process, for example, evacuation rate and time, affects the film formation and provide detailed insight into traced PL and reflection transients extracted from sub‐second videos of each channel. Based on correlative analysis between the transients and, for example, perovskite ink composition, wet‐film thickness, or evacuation time, key regions which influence crystal quality, film morphology, and are base for prediction of solar cell performance are identified.

All-fiber reflective single-pixel imaging with long working distance

We demonstrate all-fiber reflective single-pixel imaging with a long working distance and large field of view. The wavelength-dependent multimode fiber speckle is generated to illuminate the object, which further ensures the compactness and stability of the system. By the collimated MMF speckle patterns and the optical fiber receiving device, we achieve reflective optical fiber single-pixel imaging with a working distance of over 5 mm and a field of view of about 9 mm2. Based on compressed sensing, we can reconstruct object images with a sampling rate of about 4 %. This work provides a method and reference for the practical applications of optical fiber endoscopic imaging with requirements for a long working distance and large field of view.

Fast THz-TDS Reflection Imaging with ECOPS-Point-by-Point versus Line-by-Line Scanning.

We built a high-speed TDS setup with the use of electronically controlled optical sampling (ECOPS), which can measure up to 1600 terahertz pulses per second. The movement of the sample was provided by two fast-speed motorized linear stages constituting the gantry. We developed a flat-bar-based metal marker approach for the synchronization of continuous line-by-line scans. We carefully compared the performance of the terahertz reflection time-domain spectroscopy (TDS) scanner operating in a slow point-by-point and a one-hundred-times faster line-by-line imaging scheme. We analyzed images obtained for both schemes for a uniform metallic breadboard with holes, as well as a glass composite sample with defects. Although the measurement time was reduced by 100 times in terms of the line-by-line scheme, the overall performance in both schemes was almost identical in terms of the defects' sizes, shapes and locations. The results proved that the proposed ECOPS TDS system can provide uniform and extremely fast scanning without any deterioration in image quality.

Recognition and analysis of fabric texture by double-sided fusion of transmission and reflection images under compound light source

Computer vision is widely used in fabric texture recognition. In this paper, a new method based on double-sided fusion of reflection image and transmission image is proposed for recognition and analysis of fabric texture. The yarn location is obtained through transmission image, and fabric texture is obtained through reflection image. The position information of weave floats obtained by gray projection on the transmission image is given to the reflection image for classification and color recognition of weave floats. In the stage of weave float classification, an improved KNN algorithm based on FCM is proposed. First, FCM is used to cluster the HOG features of the two types of floats respectively to obtain new cluster centers, and then KNN is used for classification to obtain the weave patterns. In the stage of color recognition, the K-means clustering algorithm is used on a single weave float to obtain the color pattern. Based on the two attributes of a single point obtained from the above two patterns, a system of bidirectional error correction is designed. Experimental results show that this method effectively improves the recognition accuracy of yarn-dyed fabrics which interlaced yarns are different colors without color and texture disturbed to the greatest extent.

Fast spatially resolved optical characterization of multi-layer CVD graphene

A new quantitative and spatially resolved optical method was developed to quickly analyze the spatial distribution of multilayer graphene grown on large flat substrates, i.e., on one or more 4″ Si wafers. An image processing analysis shows that the background-corrected reflection image of graphene on the flat substrate can be normalized so that the highest image intensity is related to the thinnest or absent layer of graphene. Which of these two most typical cases is in effect for a given sample can be easily determined by a calibration wafer using laser Raman spectroscopy 2D/G peak intensity ratio. We show that the spatial distribution of multilayer graphene can be determined by relating reflected light intensity from an intensity-calibrated reflection image to the layer numbers of a local graphene film. By dividing the greyscale reflection intensity into bins, the spatial multilayer graphene distribution can be visualized with a false-colored contour plot where each graphene layer quantity is represented by a unique color for easy visualization of their spatial distribution regions. The spatial distribution over extended spatial regions of multilayer graphene grown on a flat substrate, for example, a Ni or Cu films on a 4ʺ Si or Ge wafer, can quickly be analyzed and visualized through this non-destructive characterization method by locally sampling and analyzing multiple regions of interest across a full spatially extended large substrate. Selected applications of this method are, for example, process uniformity and quality optimization for one or more large Si wafers grown in a single batch or different batches, as well as for fast and non-destructive automated multilayer graphene growth quality control methods.

Freeform Wide Field-of-View Spaceborne Imaging Telescope: From Design to Demonstrator.

Wide field-of-view imaging optics offer a huge potential for space-based Earth observation enabling the capture of global data. Reflective imaging telescopes are often favored, as they do not show chromatic aberrations and are less susceptible to radiation darkening than their refractive counterparts. However, the main drawback of reflective telescopes is that they are limited with respect to field-of-view while featuring large dimensions. We propose the use of freeform optics to maximize the field of view while maintaining diffraction-limited image quality and minimizing system dimensions. In this paper, we present a novel freeform wide field-of-view reflective telescope, starting from the optical design, and continuing to tolerancing analysis and manufacture, towards a proof-of-concept demonstrator. The novel telescope features a full field-of-view of 120° while showing an exceptional spatial resolution of 2.6 km and fitting within 1 CubeSat unit. To the best of our knowledge, this is the widest field-of-view that has ever been realized for a space-based telescope, nearly reaching Earth observation from limb to limb from an altitude of about 700 km. We hope this design paves the way for future space missions enabling improved Earth observation and leading to enhanced monitoring of climate and climate change.

Dual interfacial engineering of a Chevrel phase electrode material for stable hydrogen evolution at 2500 mA cm−2

Constructing stable electrodes which function over long timescales at large current density is essential for the industrial realization and implementation of water electrolysis. However, rapid gas bubble detachment at large current density usually results in peeling-off of electrocatalysts and performance degradation, especially for long term operations. Here we construct a mechanically-stable, all-metal, and highly active CuMo6S8/Cu electrode by in-situ reaction between MoS2 and Cu. The Chevrel phase electrode exhibits strong binding at the electrocatalyst-support interface with weak adhesion at electrocatalyst-bubble interface, in addition to fast hydrogen evolution and charge transfer kinetics. These features facilitate the achievement of large current density of 2500 mA cm−2 at a small overpotential of 334 mV which operate stably at 2500 mA cm−2 for over 100 h. In-situ total internal reflection imaging at micrometer level and mechanical tests disclose the relationships of two interfacial forces and performance of electrocatalysts. This dual interfacial engineering strategy can be extended to construct stable and high-performance electrodes for other gas-involving reactions.

Cross-Well Reflection Imaging at the Verkhnekamskoe Potash Deposit

Abstract —We propose the technique of extended processing of cross-well seismic data for reflection imaging. Based on the analysis of the wave field and synthetic modeling, a graph for processing cross-well data is developed to separate the reflections in the presence of a boundary of a sharp change in the velocity of elastic waves. The migration of the reflected waves from the time scale to the depth is performed by solving a forward problem for each source–receiver pair. As a result, the position of the reflection points is calculated, after which all the traces are stacked based on the binning grid. The input information for performing migration and solving a forward problem is the velocity characteristic of the massif, which is calculated using traveltime tomography on direct body waves obtained from the same data set of cross-well survey and vertical seismic profiling. The resulting depth seismic section has a much higher resolution than that of vertical seismic profiling and ground-based shallow seismic studies. This opens up the opportunity of identifying different small natural or technogenic objects in the interwell space.

A Plasma Transmitting Source for Borehole Acoustic Reflection Imaging.

The detection depth of current borehole acoustic reflection imaging is only tens of meters without high resolution. This considerably limits its wide application in the identification and fine description of unconventional reservoirs and in the optimization of drilling trajectories. Increasing the directional energy from the transmitter to a geological structure is an excellent way to solve this issue. In this study, a plasma source with a parabolic reflector was introduced during borehole acoustic reflection imaging. First, an experimental system was built for testing the plasma source. Next, the acoustic-electrical characteristics and directional radiation of the source were studied using experiments and a numerical simulation. Finally, the advantages, disadvantages, and feasibility of the plasma-transmitting source were analyzed; some suggestions for further work on the source and its logging application were proposed. The experimental and simulation results show that the use of a plasma source with a parabolic reflector can increase the detection depth of borehole acoustic reflection imaging to hundreds of meters with high resolution. This is crucial in imaging the geological structures near boreholes and enhancing oil–gas exploration and development.

Borehole radiation and reception responses for azimuthal shear-wave reflection imaging with an off-centred dipole acoustic tool

Abstract Radiation and reception responses of a dipole acoustic logging tool placed eccentrically in borehole fluid are an interesting and important topic in acoustic reflection imaging. Herein, we present a thorough research study on these responses. We treat the wave incidence from the reflector as the radiation from a virtual source and use the cylindrical-wave expansion method to solve both the wave radiation and reception problems for the off-centred tool, which, by using the steepest-descent method, yields asymptotic solutions for modelling the radiation and reception wavefield characteristics. The modelling results from the analytical solution and the 3D finite-difference method were in good agreement. Specifically, we analysed the radiation directivity of an eccentric dipole source in a fluid-filled borehole. The results revealed that the radiation pattern was asymmetric with respect to the borehole, and the asymmetry was determined by the eccentric distance, source frequency and formation properties. In particular, for the typical 3 kHz dipole logging frequency, the radiation was stronger in the off-centred direction than in the opposite direction. The asymmetry of the eccentric radiation resulted in a significant amplitude difference relative to its centred counterpart, which provided a potential method for addressing the 180° azimuth ambiguity of the dipole source. We used a theoretical waveform modelling example to demonstrate this advantage. Therefore, the results of this study provide a theoretical foundation for the development and application of dipole shear-wave imaging technology.

High-speed wide-field photoacoustic microscopy using a cylindrically focused transparent high-frequency ultrasound transducer

Combining focused optical excitation and high-frequency ultrasound detection, optical-resolution photoacoustic microscopy (OR-PAM) can provide micrometer-level spatial resolution with millimeter-level penetration depth and has been employed in a variety of biomedical applications. However, it remains a challenge for OR-PAM to achieve a high imaging speed and a large field of view at the same time. In this work, we report a new approach to implement high-speed wide-field OR-PAM, using a cylindrically-focused transparent ultrasound transducer (CFT-UT). The CFT-UT is made of transparent lithium niobate coated with indium-tin-oxide as electrodes. A transparent cylindrical lens is attached to the transducer surface to provide an acoustic focal line with a length of 9 mm. The excitation light can pass directly through the CFT-UT from the above and thus enables a reflection imaging mode. High-speed imaging is achieved by fast optical scanning of the focused excitation light along the CFT-UT focal line. With the confocal alignment of the optical excitation and acoustic detection, a relatively high detection sensitivity is maintained over the entire scanning range. The CFT-UT-based OR-PAM system has achieved a cross-sectional frame rate of 500 Hz over the scanning range of 9 mm. We have characterized the system’s performance on phantoms and demonstrated its application on small animal models in vivo. We expect the new CFT-UT-based OR-PAM will find matched biomedical applications that need high imaging speed over a large field of view.

Real-time realistic computer-generated hologram with accurate depth precision and a large depth range.

Holographic display is an ideal technology for near-eye display to realize virtual and augmented reality applications, because it can provide all depth perception cues. However, depth performance is sacrificed by exiting computer-generated hologram (CGH) methods for real-time calculation. In this paper, volume representation and improved ray tracing algorithm are proposed for real-time CGH generation with enhanced depth performance. Using the single fast Fourier transform (S-FFT) method, the volume representation enables a low calculation burden and is efficient for Graphics Processing Unit (GPU) to implement diffraction calculation. The improved ray tracing algorithm accounts for accurate depth cues in complex 3D scenes with reflection and refraction, which is represented by adding extra shapes in the volume. Numerical evaluation is used to verify the depth precision. And experiments show that the proposed method can provide a real-time interactive holographic display with accurate depth precision and a large depth range. CGH of a 3D scene with 256 depth values is calculated at 30fps, and the depth range can be hundreds of millimeters. Depth cues of reflection and refraction images can also be reconstructed correctly. The proposed method significantly outperforms existing fast methods by achieving a more realistic 3D holographic display with ideal depth performance and real-time calculation at the same time.

A fast and effective algorithm for specular reflection image enhancement

A fast and effective algorithm for specular reflection image enhancement

Real-time holographic lensless micro-endoscopy through flexible fibers via fiber bundle distal holography

Fiber-based micro-endoscopes are a critically important tool for minimally-invasive deep-tissue imaging. However, current micro-endoscopes cannot perform three-dimensional imaging through dynamically-bent fibers without the use of bulky optical elements such as lenses and scanners at the distal end, increasing the footprint and tissue-damage. Great efforts have been invested in developing approaches that avoid distal bulky optical elements. However, the fundamental barrier of dynamic optical wavefront-distortions in propagation through flexible fibers limits current approaches to nearly-static or non-flexible fibers. Here, we present an approach that allows holographic, bend-insensitive, coherence-gated, micro-endoscopic imaging using commercially available multi-core fibers (MCFs). We achieve this by adding a partially-reflecting mirror to the distal fiber-tip, allowing to perform low-coherence full-field phase-shifting holography. We demonstrate widefield diffraction-limited reflection imaging of amplitude and phase targets through dynamically bent fibers at video-rate. Our approach holds potential for label-free investigations of dynamic samples.