Coherent illumination of an optically rough surface creates random phase variations in the reflected electric field. Free-space propagation converts these phase variations into irradiance variations in both the pupil and image planes, known as pupil- and image-plane speckle. Infrared imaging systems are often parameterized by the quantity Fλ/d, which relates the cutoff frequencies passed by the optical diffraction MTF to the frequencies passed by the detector MTF. We present both analytical expressions and Monte-Carlo wave-optics simulations to determine the relationship between image-plane speckle contrast and the first-order system parameters utilized in Fλ/d (focal length, aperture size, wavelength, and detector size). For designers of active imaging systems, we provide input on speckle mitigation using Fλ/d to consider in system design.

The optimal viewing distance limits the movement range of the observers. We report a dual-view one-dimensional integral imaging display based on a compound parallax barrier. The elemental images I and II are displayed on the left and right of an organic light-emitting diode, respectively. The sub-polarizers I and II polarize the light rays emitted from the elemental images I and II, respectively. The compound parallax barrier consists of three kinds of parallax barriers. Two invariable parallax barriers are in the middle of the compound parallax barrier. The other parallax barriers are on the left and right of the compound parallax barrier and are denoted as variable parallax barriers I and II, respectively. The pitches of the variable parallax barriers I and II are variable. The invariable parallax barriers determine the widths of the primary viewing zones I and II. The observers with polarizer glasses I only watch three-dimensional (3D) image I, and those with polarizer glasses II only watch 3D image II. The optimal viewing distances I and II are easily adjusted by changing the pitches of the variable parallax barriers I and II, respectively.

The gamma distortion of a structured light system significantly reduces the measurement accuracy. A gamma correction method based on an attention U-Net deep neural network is proposed in this work. The mapping relationship between the wrapped phase obtained by a three-step phase-shifting algorithm and the wrapped phase obtained by a 12-step phase-shifting algorithm is established by the learning capability of the attention U-Net network model. Pixel-wise error correction of the wrapped phase maps is enabled by this method. To validate the effectiveness of the proposed method, the relationship between the number of phase-shifting steps and the nonlinear phase error was analyzed experimentally. Phase correction and 3D point cloud reconstruction experiments were carried out. It was proved that the proposed method eliminates the need to analyze the complex mathematical model of the gamma distortion, which reduces the nonlinear phase error by three times without increasing the number of fringe frames. Compared with the traditional three-step phase-shifting algorithm and the active pre-correction method, the 3D reconstruction accuracy was effectively improved by the proposed method.

Digital image correlation (DIC) measurement methods are widely accepted in the field of aeroengine blade measurements. However, there are many factors affecting the accuracy of DIC in engine blade high-temperature measurements, such as thermal radiation and thermal disturbance. To solve these problems, we propose an image preprocessing method to improve the accuracy of high-temperature DIC measurements. A series of high-temperature experiments are performed. The experimental results show that the proposed method can effectively eliminate the influence of thermal radiation and thermal disturbance caused by the high-temperature environment. The method reduces the displacement error, which can be eliminated by ∼70%. Experimental results verified the effectiveness of the proposed method.

The fastener plays a critical role in ensuring the stability and safety of modern engineering structures. However, factors such as vibration, shock, temperature changes, and others can cause fasteners to become loose, thereby compromising the stability and safety of the overall structure. Currently, fastener inspection is primarily done manually, and there is no widely adopted automatic method for real-time detection of fastener looseness. We proposed a fastener looseness inspection method based on digital shearing speckle pattern interferometry (DSSPI) and convolutional neural network (CNN). The key distinction between our proposed method and traditional vision-based methods is that our approach can identify loose fasteners without relying on direct visual observation of the fasteners themselves. Our approach involved setting up a DSSPI system to capture shearing speckle patterns, and the CNN model automatically extracted features from these images and classified them to detect loose fasteners. Principle-validation experiments were conducted to verify the feasibility of the methodology. The trained model achieved a classification accuracy of 92.57%, with a resolution of 0.04 mm and a completion time of only 2.03 ms for a single judgment. That is quite accurate, more sensitive, and much faster than the three-dimensional vision-based method. Furthermore, our proposed method has strong robustness to ambient light, while the incorporation of Random Erasing technology enhances robustness to part occlusion or damage of the measured surface. Most notably, our method can detect loose fasteners before deformation, a capability that conventional vision-based methods lack. These findings demonstrate the tremendous potential of our method for real-time inspection of fastener looseness.

We report the development and working of a compact rubidium atom magneto-optical trap (MOT) operated with a hollow pyramidal mirror and a single laser beam. This type of compact MOT is suitable for developing portable atom-optic devices as it works with a smaller number of optical components compared with the conventional MOT setup. The application of this compact MOT setup for pressure sensing has been demonstrated.

In millimeter-wave imaging systems, the inversion efficiency of both the narrowband and broadband systems is affected by the target’s distribution distance. The mismatched distances cause inefficiency of the system, and the recovered images suffer from displacement blur. We analyze in detail the reasons for this phenomenon and propose a simple method to overcome it. Minimizing the sharpness metric of images is a key strategy to solve this problem. Using this method, the exact range information of the target can be obtained from the minimum sharpness of the unknown object, and then, the region of interest of the inversion can be located. Both synthetic and full-wave simulation data demonstrate the superiority of the method. Finally, the efficiency of the method is verified by the in-house developed test system.

To address the segmentation errors caused by the difficulty of determining the threshold values in the conventional method, an automatic segmentation method is proposed in this paper that uses both the object image pattern of the measured gear tooth flank and the modulation values obtained from the interference fringe patterns (IFPs). This segmentation method is integrated into the matching step. The matching step establishes the correlation between the image and the actual gear tooth flank by matching the simulated gear tooth flank image to the real one. First, pixel columns are extracted from both the object image pattern and the IFPs at a specified interval. Then, the boundary points of each column are located by the gray values. Second, the boundary points are optimized by the modulation values and the boundary curves of the gear tooth flank region are fitted by these boundary points. Finally, the simulation gear tooth flank image is matched with the boundary curves of the gear tooth flank region, resulting in the final segmented tooth flank region. The proposed method is verified in several IFPs, and the results show its feasibility and accuracy.

The Fourier transform (FT) method is one of the foremost single-fringe techniques for high-speed three-dimensional (3D) surface reconstruction within the fringe projection profilometry (FPP). Despite its widespread use, the intrinsic issue of spectrum leakage in the FT method leads to diminished precision in regions of image edge. We introduce a spatial-domain phase-shifting (SDPS) method, employing pixel spatial translation to extract the phase-shifting subfringe sequence, followed by the least-square fitting technique to accurately determine surface phase information. Simulation analyses for continuous and discontinuous structures are conducted to affirm that the SDPS method could mitigate the edge error in comparison to the FT method. Meanwhile, the factors that may influence the performance of the proposed method are also analyzed, including the background, modulation, and spatial translation distance. Experiments of static and dynamic scenarios are carried out to further demonstrate that the SDPS method could achieve improved measurement precision in edge areas when compared with the FT method and has the potential to be applied in dynamic 3D surface reconstruction with high precision and efficiency in FPP.

In traditional calibration methods for line-structured light vision sensors, the use of two-dimensional planar targets usually requires multiple placements of the target in the measurement space to capture more images to improve the final calibration accuracy, which complicates the calibration process. We propose a new calibration method for line structured light vision sensors (LSLVS) based on freely placeable circular targets. The circular target only needs to be placed freely twice, and the camera captures the images of the circular target and the optical strip. Based on the geometrical relationship of the circle under the camera projection and the nature of the vanishing line, the target plane is first reconstructed, and then multiple three-dimensional points on the target plane are obtained according to the perspective projection relationship, and finally the reconstruction of the optical plane is completed. Compared with the traditional calibration method, this method can be applied to measurements in a limited space, and it does not need sophisticated auxiliary equipment to control the target motion during the whole calibration process, which makes the calibration process more simplified. The final experimental results show that the method can reach an accuracy of 0.0523 mm when only two images are used and can be effectively applied to the line structured light measurement system.

The previous demonstrations of optical reservoir computing (ORC) primarily utilized theoretical dynamic systems. Here, we explore the practical application of ORC in analyzing real-world financial datasets. In terms of prediction accuracy, a comparative analysis is conducted between ORC and its conventional counterpart implemented on a desktop. The results indicate that both models exhibit similar performance levels. Notably, the ORC model, equipped with a reasonably sized reservoir state, demonstrates commendable prediction accuracy. We provide valuable insights into the feasibility and effectiveness of ORC in handling real-world time series data, contributing to the broader understanding of its practical applications.

Right dihedral-angle error is key in cube blocks such as corner cube retroreflectors in laser ranging and cube test mass in space-borne gravitational reference sensors. A high-precision comparison method of dihedral-angle using optical differential wavefront sensing is proposed. The principle is to use an optical interferometer to measure the relative wavefront signal of two light beams reflected from two surfaces containing the angle. The relative dihedral angle error of the two samples can be obtained by comparing the two dihedral wavefront differences. Compared with conventional optical methods such as the Fizeau interferometer and autocollimation, this method has the advantages of low cost, simple data processing, compactness, and high accuracy. An interferometer for relative right dihedral-angle error measurement is built and tested. The experimental results show that an accuracy below ±6 μrad within a dynamic range of ±100 μrad has been achieved. Combined with a dihedral-angle standard sample, this method can be widely used for dihedral-angle comparison and calibration.

Radiometric information offers valuable insights into the surface and material properties of remote targets. Such information can be obtained along with the surface geometry by laser scanning. However, local variations in the surface geometry and orientation can introduce a bias in the radiometric data, related to the angle of incidence (AoI). We demonstrate a supercontinuum-based hyperspectral laser scanning approach for high-precision distance measurements, and its applicability to mitigate the AoI effect by enabling an enhanced data-driven radiometric correction of the acquired intensities. Our experiments utilize a supercontinuum (SC) spectrally broadened to 570 to 970 nm from a 780 nm frequency comb. Distance measurements are derived from the differential phase delay of the intermode beat notes, while the backscattered reflection spectrum is captured using a commercial spectrometer over the spectral range of the SC output. We obtain hyperspectral point clouds with sub-mm range noise on natural targets (gypsum board and leaves of a plant used herein) placed at a distance of 5 m. The high-precision range measurements allow for correctly estimating the surface orientation and modeling the impact of the AoI on the acquired radiometric data. The estimated model is applied to correct the acquired hyperspectral signatures, which are further exploited to compute various vegetation indices commonly used as plant health indicators. Our results illustrate enhanced information content on the direct three-dimensional mapping of such spectral data of plant leaves with a reduced AoI bias. These results highlight new opportunities for future research into remote sensing of vegetation and material probing with increased sensitivity.

For a fringe projection profilometry, the projector calibration is the key step to ensure the measurement accuracy of the system. However, conventional methods for the projector calibration are usually involved a complex system model and a calibration process. Therefore, an approach for accurate projector calibration based on the Grey Wolf Optimization (GWO) algorithm and the multi-layer perceptron (MLP) is proposed to simplify the process and improve the generalization. In this method, in order to compensate the errors of projected image coordinates of the calibrated corners obtained by using the projective transformation matrix, the parameters of the MLP network are optimized by using the GWO to construct the GWO-MLP network. Then, it is trained to compensate the errors of the coordinates of characteristic corners and is available to calibrate the projector. The experiments verify the feasibility and effectiveness of the proposed method.

We explore the concept of spoof surface plasmon polaritons (SSPPs) as a means to confine plasmons on the surface of a tiny metallic structure. We focus on introducing an efficient transition design that confines the SSPP wave along a corrugated metallic strip with metal acting as a ground material. To achieve this, a unique unit cell specifically designed for waveguiding purposes was analyzed. The dispersion characteristics of this design were presented, demonstrating its potential for SSPP waveguiding applications. By varying the groove height from h1 to h7 (ranging from 0.5 to 3.5 mm), the SSPP waveguide was developed and analyzed its spectral characteristics through corresponding S parameters. Furthermore, the effects of altering the corrugated groove width from 1 to 2 mm was investigated. This variation is shown to have a linear impact on the gain, with a maximum gain of 7.71 dBi observed.

In intelligent transportation systems, distributed acoustic sensing offers unparalleled advantages in monitoring and analyzing vehicle characteristics and behaviors in real time over the entire optical fiber. In this work, an accurate and efficient φ-optical time domain reflectometer-based load recognition method for light and heavy loaded vehicles is proposed. Before load recognition, wavelet denoising and 1D-mean filtering methods are used to denoise the signals; then the Mel spectrograms of the signals are extracted as the features input to the load recognition model with a backbone of EfficientNet convolutional neural network. The validation results show that, using an ∼47 km sensing optical fiber, the recognition of light and heavy loaded vehicles can well meet the needs of real-time data analysis and decision making of intelligent transportation, with an average recognition accuracy of 97.81% within 14 ms for each recognition.

We present a design of a fully electrically tunable metasurface switch based on nematic liquid crystal (LC). By applying different voltages on adjacent gratings of the interdigitated electrodes, the dielectric constant of the LC material and the responses of the proposed metasurface can be arbitrarily tuned. The experimental results reveal a reflective switch action in the structure across a frequency range of 106.80 to 114.15 GHz. The maximum operational frequency bandwidth is 7%, and the highest switch contrast ratio achieved is 0.77. Moreover, the suggested structure demonstrates multifunctional switching capability, manifesting a transmissive switching effect in the frequency range of 340.75 to 345.13 GHz. The measured switch contrast ratio reaches a maximum of 0.71. Combining the advantages of multifunctionality and cross-spectrum application, we provide an innovative approach for developing switches intended for terahertz wave communication systems.

Extended Kalman filter (EKF) is a popular method to address the fast rotation of the state of polarization and large polarization mode dispersion in coherent optical communication. But it is usually underperforming in high-order modulation. Radius-directed idea is introduced to enhance the performance of EKF-based method. We call the proposed scheme radius-directed extended Kalman filter (RD-EKF). The performance of the proposed Kalman scheme is verified both in the polarization-division multiplexed 16QAM and 64QAM system. By the results, the RD-EKF scheme has better performance and less complexity than conventional EKF method in the high modulation format system.

A thulium-doped (Tm3+) optical fiber amplifier (TDFA) module operating in the E-band is proposed. The bandwidth limitation inherent in E-band amplifiers employing rare-earth element doping is mitigated through the utilization of the amplifier module designed with a parallel combination of the two TDFAs. The performance of the amplifier is effectively analyzed through the optimization of parameters including TDF length, Tm3+ density, doping-radius of Tm3+, numerical aperture, and input signal power to the TDFAs. An average gain of 37.12 dB and a noise figure <3.93 dB are obtained in the wavelength region of 1412 to 1460 nm with a maximum of 41.54 dB at 1432 nm having a moderately uniform gain. The impact of the nonlinear ion–ion interaction mechanism (IM) on the signal is also investigated for the designed amplifier module. Having obtained the optimized parameter set, the percentage increase of 0.029% and decreases of 0.043% in the signal gain at the wavelengths of 1420 and 1448 nm, respectively, are obtained considering the IM effects.