The theoretical atmospheric refractivity model, which based on the standard atmosphere, fails to reflect the volatility of the actual atmospheric refractivity. To solve this problem, an atmospheric refractivity estimation method is proposed according to stellar light deflection. Firstly, based on the stellar observation data of optical satellite, the stellar light deflected by atmospheric refraction is analyzed. An optical path model of which stellar light enters the optical satellite sensor after being refracted by the atmosphere is established. The symmetry of the optical path model is proved under the assumption of layered spherical atmosphere. Secondly, an iterative forward feedback method is proposed by measuring stellar light and theoretical stellar light, which can estimate the layered atmospheric refractivity. Finally, the method is validated using the stellar observation data. The calculated atmospheric refractivity agrees with the theoretical one, and shows the short-term volatility. The results of the experimental data show that more than 88% of the estimation error between the theoretical sight and the measured one is within 1%, and the remaining is no more than 20%.

A particle swarm optimization algorithm (PDW-PSO), of which the inertia weight is modulated by particle position, is proposed for step-by-step optimization. The diffraction efficiency is calculated using rigorous coupled wave analysis (RCWA), and structural parameters of gratings are optimized. The comparison among PDW-PSO, traditional particle swarm optimization of which the inertial weight is unchanged (PSO), and particle swarm optimization of which the inertia weight is iteration-determined (IDW-PSO) shows that PDW-PSO has a faster convergence rate. Compared with PSO and IDW-PSO, the average number of iterations of PDW-PSO decreases from 89.83 and 74 to 21.2, and the number of calling RCWA drops from 3144.05 and 2590 to 224. The influence of wavelength matching number on the algorithm is analyzed. The magnification of RCWA calling numbers of PSO and IDW-PSO is equal to that of wavelength fitting number, while the magnification of RCWA calling numbers of PDW-PSO is less than that of wavelength fitting number. Experiments on algorithm accuracy are carried out. In 30 runs, PDW-PSO, PSO, and IDW-PSO have similar times of correct convergence to the optimal value, and the error is less than 6.6%. With the increasing particle number, the accuracy of the three methods improves, and the algorithm can be guaranteed to converge to the right optimal value after the particle number increasing to 27.

Layered spatial modulation technique is introduced into free space optical communications. A layered optical spatial modulation (LOSM) system suitable for turbulent channels is proposed by simultaneously activating two lasers using pulse position modulation (PPM) and pulse amplitude modulation (PAM), respectively. The principle of layer mapping and bit mapping is described in detail, based on which the bit error rate expression of the proposed LOSM system is derived, and the Monte Carlo simulation is utilized to verify its reliability. The simulation results show that the LOSM system can greatly improve the spectral efficiency of the system. For example, the spectral efficiency of the (5,4,2,4)-LOSM system is more than 9 times that of the (8,4,16)-SPPM (spatial pulse position modulation) system for the same transmission rate. When the spectral efficiency is 4 bit·s-1·Hz-1, the transmission rate of the (5,4,2,4)-LOSM system is nearly twice that of the (8,4,2)-SPAM (spatial pulse amplitude modulation) system, and the two systems have the same bit error performance.

In free space, an orbital angular momentum (OAM) beam can be affected by atmospheric turbulence, which distorts the beam’s spiral phase and degrades the signal quality after demodulation. To study the effects of different conditions of atmospheric turbulence on orthogonal frequency division multiplexing (OFDM)-OAM optical signals, a non-Kolmogorov turbulence model is used to simulate atmospheric turbulence by varying the refractive-index structure constantCn2 and atmospheric index α. The intensity profile of a demodulated Gauss beam as well as the light intensity and bit error rate of an OFDM-16QAM signal carried by an OAM beam are tested experimentally. Variations of Cn2 and α affect the Gauss beam and the detected OFDM signal while channel coding reduces the effect of turbulence to some extent.

Based on spectra measured by the open-path Fourier transform infrared (OP-FTIR) spectroscopy technology, the two-dimensional concentration distribution of the gas in a Gaussian spatial distribution model was reconstructed using the algebraic reconstruction technique (ART) and the maximum-likelihood expectation-maximization (MLEM) algorithms. Two evaluation indexes, the nearness and the correlation coefficient, were used to analyze the reconstructive accuracy and anti-noise performance of the reconstruction algorithms. In the single-peak concentration field of the gas, the nearness of the ART and MLEM results were 0.177 and 0.044, respectively, while they were 0.263 and 0.069, respectively, in the double-peak concentration field. The results therefore indicate that MLEM is more suitable for complex concentration distributions. Conversely, at different noise levels, the anti-noise performance of ART is better than that of MLEM, which is more sensitive to noise.

This paper presents a novel approach to generate computer-generated holograms (CGHs) with orthogonal scanning multi-view projections. An unified object three-dimensional Fourier spectrum sampling model is established, and based on its error analysis, the spectrum sampling circle of a circular scanning projection image at a specific angle θ can be simulated from a traditional orthogonal scanning projection image; then, the principle of "smaller θ (view angle of scanning) wins all" is adopted to determine the spectrum sampling information for overlapped positions so as to improve the spectrum utilization efficiency of orthogonal scanning projection image. Starting from the relationship between the ideal sampling point and its integration points in the consistency of spectrum information and the degree of spatial proximity, we set the weights of frequency-domain grid points where the ideal sampling points are located. Based on these weights, grid points with high consistency of spectrum information are selected adaptively as the actual sampling points, thereby achieving a balance between the sufficient sampling of projection spectrum and the introduction of background noise to obtain the optimal object three-dimensional Fourier spectrum. Experimental results of CGH with the orthogonal scanning multi-view projection for a virtual three-dimensional model show that the visual quality of the reconstructed hologram by the proposed method is notably improved. The signal-to-noise ratio of the reconstructed hologram is significantly better than that of traditional orthogonal and circular scanning methods under the same number of projected images; in addition, the signal-to-noise ratio of the reconstructed hologram implemented with a redundant sampling operation by the proposed method is also better than that of the traditional orthogonal method even when the number of projected images is reduced by one time. Therefore, the proposed method has great values both on theory and practice.

In order to enhance the accuracy and robustness of multispectral face registration results suffering from non-rigid deformation, noise, and outliers, a multispectral face registration method based on the spatial geometrical structure and local shape features of feature points is proposed. On the one hand, we use inner-distance shape context as the local shape feature of the point set, and create the similarity measure function between visible and infrared images. On the other hand, a Student's-T mixture model is used to represent the transformation model estimation in non-rigid point set registration process, and the model can be solved by using the expectation maximization algorithm. The simulation results show that the proposed method can realize exactly registration of point sets with deformation, noise,and outliers. The visible and infrared real image databases demonstrate that the matching error and computing efficiency of the proposed method outperform those of the comparison methods. As a result, the multispectral face images after registration and fusion will improve the performances of follow-up face detection and recognition.

Based on the properties of Mojette projection transform in spatial and frequency domains, we propose a limited-angle computed tomography (CT)reconstruction algorithm with minimum redundancy coverage in the frequency domain. The minimum redundant coverage corresponds to the minimum spatial projection sampling (i.e., the reconstructed image has minimum number of projections with maximum efficiency). The equivalent relationship of the Mojette projection data in its frequency domain is determined. The limited-angle CT image reconstruction can be achieved by compressing the projections into a limited angular range. Experimental results show that high-quality reconstructed images can be obtained by using the proposed algorithm.

Aiming at the problem of non-line-of-sight imaging under incoherent illumination, we propose a solution based on deep learning. Combining the classical semantic segmentation and residual model in the field of computer vision, a URNet network structure is constructed and the classical bottleneck layer structure is improved. The experimental results show that the improved model has more details of recovery images and generalization ability. Compared with speckle autocorrelation imaging method under incoherent illumination, the recovery performance of this method is greatly improved.

Aiming at improving the quality of the neutron computed tomography (CT) reconstructed from high noise and sparse angle projection data, an iterative reconstruction method (SIRT-WTDM) combined the simultaneous iterative reconstruction technique (SIRT) and weighted total difference minimization (WTDM) is successfully proposed. The reconstructed images obtained by algebraic reconstruction technique, simultaneous algebraic reconstruction technique, and SIRT are compared with or without the random noise in the projections, from which the SIRT method is proved to have higher reconstruction accuracy and stronger anti-noise ability. Therefore, the SIRT method is adopted as the fidelity term of the neutron CT iterative reconstruction method with high-noise projections. Considering the constraint to the sparsity and the continuity of the image gradient, the WTDM method is adopted as the regularization term of the neutron CT iterative reconstruction method. Under the condition of extreme sparse angle projections, the SIRT-WTDM can obtain the better reconstruction images, which has been proved by the Shepp-Logan simulated data and cold neutron CT scanning data.

Structured light illumination imaging has important applications in three-dimensional(3D) measurement of close-range high-resolution objects. Based on traditional structured light illumination imaging, a dynamic background light interference suppression technology based on invisible structured light three-dimensional imaging is proposed, a 3D contour of an actual target is acquired, and the anti-interference ability of dynamic background light is analyzed and studied in detail. The generation of structured light is based on the principle of laser interference. The emitting side projects two orthogonally polarized beams, and no interference fringes are generated on the surface of the object. The receiver uses synchronous phase shifting technology to achieve the detection and reconstruction of the structured light stripe. Based on the synchronous phase shifting technology, a four-step phase shifting fringe image is obtained simultaneously, the background light interference can be effectively reduced, and the dynamic 3D imaging capability is improved. In this paper, we theoretically analyze the principle of invisible structured light imaging and the mechanism of dynamic background light suppression, establish an experimental verification device, and obtain a 3D reconstructed image of the actual target under dynamic background light interference. The experimental results are in agreement with the theoretical analysis results.

This study investigates the characteristics of the three-channel output interference signals from a fiber Mach-Zehnder interferometer based on a 3×3 coupler. The phase-fading problem is solved using a scheme that judges the positive and negative feedback based on the orthogonal signals. The LabVIEW software is used to realize the acquisition of orthogonal signals and the processing of feedback output signals. Measurement and analysis reveal that when the feedback signal is directly output, the interference signal briefly deviates from the stable point. The whole process requires approximately 35 ms. However, the proposed feedback-judgment scheme reduces the phase-stabilization time to approximately 18 ms. An optical-fiber collimation focusing system directs the light to the surface of the test object and receives the reflected light. A high-frequency (1.5 MHz) vibrational signal consistent with the input signal frequency is detected. The feasibility and effectiveness of the proposed feedback-judgment scheme and designed interference system are verified.

Traditional methods for mixed-particle classification usually extract particle features from binary images. After designing appropriate features according to the particle type, particles can be classified using widely known classifiers, such as back-propagation neural network and support vector machine (SVM). However, classifying touching particles is a challenging, and inappropriate feature design may further reduce the classification accuracy. Herein, a convolutional neural network (CNN) is utilized to extract the features for building mixed-particle image classifiers. In particular, particle locations in an image are determined using a region proposal network. Furthermore, a classifier is designed and combined with a fully convolutional network to achieve pixel-level particle segmentation. Experimental analysis is performed on some flowing-mixed-particle systems comprising spherical, elongated, and irregular particles. According to the analysis results, SVM method using manually designed features can achieve an average precision of 87% and recall of 87%, whereas those of the CNN-based method are up to 97% and 93%, respectively. The latter method can also reduce the analysis error by more than 11% for number median diameter (Dn50) of irregular particles. In addition, several shortcomings in traditional methods, such as the need for manually designed features are solved, making it easier to build an end-to-end system for effective real-time image analysis of flowing mixed particles.

Reducing the impact of optical aberrations and random noise on the accuracy of star centroid location extractions is difficult using traditional centroid algorithms. To solve this problem, the star image of a star sensor is analyzed herein and a star sensor centroid localization algorithm based on star image resampling is proposed. The algorithm employs the modulation transfer function of the star sensor optical system and pixel frequency response characteristics of the image sensor. The point spread function of the defocused optical system is calculated based on the Fraunhofer diffraction theory, and the systematic error of the resampling-based centroid algorithm is simulated. Simulation results show that the root mean squares of the systematic errors under different aberration conditions are <0.01 pixel. Results of the error-measurement experiments of centroid extraction system performed on a star sensor show that the systematic error of the resampling-based centroid algorithm is 0.008 pixel, which is 66% lower than that of the traditional sinusoidal curve compensation method. The proposed algorithm has high precision and is not affected by the aberrations of the optical system; therefore, it is an effective method for improving the accuracy of star sensors.

Micro-lens array method is one of the widely utilized approaches to realize beam homogenization. This method can achieve large-area uniform spots in the focal plane by changing the focal power of the imaging lens. Herein, the feasibility of the scattering imaging method is analyzed theoretically and experimentally. In order to accurately measure the illuminance of spots in the focal plane, the mathematical relationship between the image gray scale value and the illuminance of spots in the target plane is established using the Zhang Zhengyou's camera calibration method, after considering the interfering factors such as the reflectivity of diffusing plate and the off-axial angle of the camera. Bidirectional reflectance distribution function of the diffusing plate is experimentally calibrated. The illuminance distributions of the homogenized spots in the focal plane and its vicinity are measured for the principal integral lenses with two focal lengths. Experimental results show that when the focal lengths of the integral lens are 300 mm and 500 mm respectively, the laser fluxes are roughly equal and the measured spot sizes are basically consistent with the theoretical values in the target plane. By comparing the variation coefficients of spot distributions in the defocus observation plane for these two cases, the optimal position to realize homogenized spot distribution is obtained.

Digs or scratches generated during the processing and application of optical components seriously affect the surface quality of these components. The scattered light caused by digs or scratches is divided into two parts based on Peterson’s defect scattering theory: geometric refraction or reflection from the surfaces inside scratches or digs and diffraction of light that passes around the scratch or dig. The analytical formulas for the bidirectional reflection distribution function of the scratches or digs are derived considering the light-blocking effect of the digs and scratches and the boundary conditions for the disappearance of diffraction around the digs, and by combining the theory of defect scattering with the new national standard of GB/T 1185-2006. Then, angular resolved scattering and total scattering are analyzed under different defect grade numbers. The results show that the total scattering of the surface defect is approximately linearly proportional to the area of the defect. On this basis, herein, a surface quality inspection method based on total scattering measurement is proposed, and the surface defect thresholds of optical components are analyzed.

An in-situ measurement method of polarization aberration (PA) in lithographic projection lens is proposed. A new characterization of PA is proposed, and a cross-correlation relationship among three Pauli terms of PA and the difference in aerial images under three pairs of orthogonal illuminated polarization states is derived. Based on this, the principal component analysis is performed on three groups of differential aerial images of alt-phase-shift mask to solve all the Pauli Zernike coefficients of PA. This paper describes the coupling of different Pauli terms theoretically in the imaging process and resolves the coupling problem through the principle of measurement based on this theory. As a result, first 37 orders of Zernike coefficients for all Pauli terms can be measured by the proposed method. In the condition of typical deep ultraviolet lithography, random PA tests of the proposed method are performed and the standard errors of 6×37 measured Pauli-Zernike coefficients (real and imaginary parts of three Pauli terms) are all in the order of 10 -3. Simulation results validate the correctness and the effectiveness of the proposed method.

In order to obtain high accuracy solar spectral irradiance in a limited sun observation window, it is necessary to ensure that the instrument has completed warm-up when the sun enters the observation window. The start time of warm-up can be predicted in real time to ensure the consistency of the warm-up. Therefore, a short-time high-precision forecast is made for the time when the sun begins to enter the instrument observation window. A method for predicting the solar angle from the current broadcast time of the satellite platform and the instantaneous root of the orbit is described in detail. Using this method, we calculate the solar angle of a sun-synchronous orbit. Te calculated results are compared with the STK simulation, indicating that the maximum angle error of the proposed forecasting method is 0.5° during the warm-up period. The maximum deviation of the warm-up time caused by the angle error is 20 s, which meets the requirement of 1 min. The main error sources of the proposed method are analyzed, which provides reference for on-orbit short-term solar angle forecast of other satellite loads.

The high-order correlation characteristics of a light field are important features for revealing the statistical behavior of light. When the traditional HBT(Hanbury-Brown and Twiss) experimental model is used to measure the multi-photon high-order correlation, the measurement is complicated because of the limited number of single-photon detectors and splitters. In this study, we propose a fast method to measure the high-order correlation of a light field using an intensified charge-coupled device. The high-order coherence of the pseudothermal and coherent light fields can be measured and analyzed by varying the exposure time and light intensity (counting rate). The results demonstrate that the high-order coherence of a light field can be determined under appropriate conditions. When the exposure time is approximately 600 ns and the counting rate is 5.12×108 s-1, the measured second-order and third-order coherences of the pseudothermal light fields are g(2)T(0)=1.79±0.20 andg(3)T(0)=4.94±0.59, respectively. Note that the coherence of up to four orders has been measured and that the results can be theoretically explained. We expect that this method can be applied for measuring and studying the high-order coherence of some light sources. Furthermore, we believe that the proposed method will significantly contribute to revealing the high-order correlations of the light fields.

This study demonstrates a simulation model of a 2.8 μm gain-switched Er∶ZBLAN fiber laser by numerical simulation. The simulation results show that there exists an optimal transmittance of output mirror, resulting in an largest output power. The coupling efficiency has significant impacts on the pulse width, peak power, and pulse shape. Accordingly, the influence of the pump power on the pulse shape is calculated and discussed. A signal pulse appears during two pump periods with a weak pump, whereas several signal pulses appear during one pump period with a strong pump. To the best of our knowledge, calculation results, such as the influence of the coupling efficiency on the output power, pulse energy, and pulse shape and the weak signal consistent with pump period when the pump power is around the threshold, have not been reported in any experiment. This study shows that a stable gain-switched pulse output in a 2.8 μm Er∶ZBLAN fiber laser can be achieved only with appropriate coupling efficiency and pump power.

A spectrally resolved scanning calibration facility based on a supercontinuum laser and monochromator (SCM) was proposed for the calibration of the absolute spectral radiance responsivity of the sensors. Two radiance meters, labeled Traps-A and Traps-B, were used herein. The absolute spectral power responsivities of the meters were traced to a cryogenic absolute radiometer. The absolute spectral radiance responsivity of Trap-B was obtained by a general unit-level calibration method, and a system-level calibration method based on the SCM with Trap-A taken as the reference. The calibration uncertainties of Traps-A and Traps-B were lower than 0.46% and 1.8%, respectively. The calibration results by the two methods were in good agreement, with a relative difference of less than 0.9% in the 450-900 nm. The results imply that a spectrally-resolved scanning calibration facility based on SCM is suitable for the absolute spectral radiometric calibration of sensors and highly applicable to the absolute spectral radiometric calibration of remote sensors.

In this work, an array optical tweezer system based on non-orthogonal binary phase plates is proposed. The proposed system can stably trap multiple particles arranged in a non-orthogonal array. The binary phase is designed through a genetic algorithm and the Fourier transform theory of a high numerical aperture (NA) objective lens under tight focusing conditions. The normalized phase turning point of the binary phase is optimized to have different beam-splitting ratios, high diffraction efficiency, and high uniformity, and then it can be used to design the non-orthogonal binary phase plate with different inclination angles. Using this binary phase plate, we can obtain a variety of non-orthogonal array spots in the focal plane of the high-NA objective lens. Furthermore, the stable trapping of silica microspheres can be realized in the experiment of optical tweezers based on the non-orthogonal array spots. Theoretical simulation and experimental results show that this method can effectively achieve the optical trapping of a non-orthogonal arrangement of a large number of particles. This technology is expected to play an essential role in the epitaxial growth of nanoparticle arrays.

We present theoretical research on the intensive electromagnetic pulse (EMP) inside a target chamber. Three types of EMP environment, including one irradiated by escaped hot electrons, one involving cavity-system-generated EMP (SGEMP), and one involving cable SGEMP, are considered based on different physical mechanisms. Further, we introduce the physical model and the numerical simulation method. The simulation is conducted based on the finite-difference time-domain method, the particle-in-cell method, and the Monte Carlo algorithm. The theoretical results are in good agreement with the experimental results. This study provides technical support for further studying on the electromagnetic phenomena in the laser-target processes and improving the electromagnetic compatibility of the devices.

An optical frequency synthesizer can output single-frequency Hz-linewidth laser with high frequency stability at a specified optical frequency within a wide spectral range. Based on a prototype of optical frequency synthesizer at 700-990 nm, we make a step towards its automatic control. The wavelength of output laser and a motorized rotation stage of a grating are set automatically after comparing the reading of a wavemeter with the target output frequency. The beat frequency signal between the output laser and femtosecond optical comb can be obtained, and automatic signal processing can be realized, obtaining phase-locked control signal between the output laser and reference laser. An error signal for laser frequency control can be obtained within one minute. This study lays a foundation for the realizing the fully automatic optical frequency synthesizer.

According to the prior knowledge about obvious quadrilateral feature of bioresorbable vascular scaffold (BVS) struts in an intravascular optical coherence tomography (IVOCT) image, this study proposes a novel algorithm based on four corners of BVS struts to automatically obtain their contours in the IVOCT imaging system. It solves the problem that dynamic programming (DP) algorithm, which is a contour-based algorithm, is not sufficiently accurate because of the in uence of the fractures inside the struts and blood artifacts around the struts. Experimental results show that the proposed algorithm achieves an average Dice's coefficient of 0.88 for the strut segmentation areas, which is increased by approximately 0.08 compared to the result obtained by the DP algorithm. This algorithm can accurately and robustly segment BVS struts in the IVOCT image, and thus it can better assist doctors in the automatic strut malapposition analysis in clinical applications.

In order to improve the accuracy and real-time performance of visual tracking in complex scenes, a real-time and anti-occlusion visual tracking algorithm based on multi-layer deep convolutional features is proposed. For the visual tracking task, the deep convolutional networks VGG-Net-19 are fine-tuned, and then the multi-layer deep convolutional features of the target region are extracted from the adjusted model. The location correlation filters are constructed to determine the target center position. In order to determine the target scale, a scale correlation filter is performed to sample multi-scale images surrounding the target region. When the target is occluded, the stage evaluation strategy is used to update and recover the model, which solves the problem of template error accumulation. The experimental results on the tracking benchmark OTB-2015 which concludes 100 video sequences and UAV123 which concludes 123 video sequences show that the proposed algorithm has higher accuracy and can adapt to complex situations such as target occlusion, appearance change and background clutters. The average speed is 29.6 frame/s, which meets the real-time requirements of the visual tracking task.

The very deep super resolution model has disadvantages: the convergence speed is low, the original image must be preprocessed before training, and the network redundancy must be reduced. This study proposes a single-image super resolution reconstruction method based on depth jumping cascade (DCSR). First, DCSR eliminates pre-processing, extracts the shallow features directly on the low-resolution image, and finally uses sub-pixel convolution to magnify the image. Second, each convolutional layer is fully utilized to extract the image features using the jump cascading block, thereby realizing feature reuse and network redundancy reduction. The jump cascading block of the network establishes a short connection directly from the output to each layer, speeding up the network convergence speed and alleviating the gradient disappearance problem. The experimental results show that on several public datasets, the peak-signal-to-noise ratio and the structural similarity of the algorithm are higher than those of existing algorithms, which fully demonstrates an excellent algorithm performance.

This study proposes an improved detection algorithm of YOLO V3 specially applied in small target detection to solve the problems of low detection and high false alarm rates of small targets in an image. The resolution of small targets is low, and their features are not obvious; thus, this study proposes 2× upsampling for the feature map down-sampled by 8× of the previous network,and the feature map upsampled by 2× is concatenated with the output of the second ResNet block unit. A feature fusion target detection layer, whose feature map is down-sampled by 4×, is established. Two ResNet units in the second ResNet block unit of Darknet53 in the YOLO V3 network structure are added to obtain more features of the small target. The K-means clustering algorithm is used to select the number of candidate anchor boxes and aspect ratio dimensions. A comparative experiment is performed based on the improved YOLO V3 algorithm on the VEDAI dataset and YOLO V3 algorithm. The results show that the improved YOLO V3 algorithm can efficiently detect small targets and improve the mean average precision and recall rate of small targets.

In the field of face recognition, pose variation is one of the significant challenges that affects the recognition performance and has been one of the major obstacles hindering the improvement of the face recognition technology. In this study, affine transformation parameters of side face and full-frontal face patches are obtained by applying the weighted Lucas-Kanade (LK) algorithm. We further propose that an optimal parameter for correcting face pose can be obtained based on the maximum Gabor similarity. Furthermore, the average Gabor similarity acquired from the optimal parameter of each face patch can be considered to be the face recognition weight, improving the recognition rate and enhancing the robustness of the pose invariant face recognition. Finally, the experimental results obtained based on the FERET face database denote that the recognition rate for the image with a pose of 45° can reach up to 97.3%, indicating that the usage of the maximum Gabor similarity as a basis for parameter extraction of the weighted LK algorithm is valid. This method can also handle illumination variations. Considering the average Gabor similarity as the recognition weight will ensure the robust and effective application of this algorithm.

PatchMatch-based algorithms that simultaneously estimate the disparities and normal unit of a disparity plane have achieved highly accurate sub-pixel disparities in the stereo matching problem; however, this kind of methods can not effectively deal with error matching in the non-texture regions of image. To solve this problem, we improve the LocalExp(local expansion move)algorithm and present a new stereo matching algorithm integrating multidimensional information for adaptive pixel category optimization. First, a crossover window is designed,the color and color self-correlation information in the window are used to establish the weight, and the restrained function is utilized to eliminate the outliers in the matching cost. Second,the constraint mechanism is added to the label initialization procedure, the proposal generation mechanism is modified, and the local expansion movement algorithm is used to optimize the label values. Finally, the pixel category information-based filling strategy is used to refine the disparity. The experimental results show that the proposed method can obtain a low matching error on the Middlebury dataset.

Herein, silver nanowires with high surface roughness are prepared via vacuum thermal evaporation and a solid-state ionics method. The nanowires are assembled into silver conductor RbAg4I5 films under the imposed current intensity, obtaining surface-enhanced Raman scattering (SERS) substrates with highly uniform, well ordered, and high-repeatability. The surface enhanced Raman characteristics of the silver-nanowire substrates with high surface roughness are detected using Rhodamine 6G (R6G) probe molecules in aqueous solution. The experimental results show that the prepared silver nanowires are branch-shaped and orderly arranged in the macro and micro structures, respectively; the fractal dimension of the silver nanostructure is 1.59. The method detects molar R6G concentration as low as 10-17 mol/L when the silver nanowires are used as SERS substrates. The prepared silver nanowires with orderly dense arrangement and high surface roughness confirm its potential applicability in environmental sciences and other fields.

In this study, a Si-Na-Zn-Al system was chosen as the glass matrix and Ce4+ and Ag+ were chosen as the photosensitive and thermal factors, respectively. The precipitation of Ag0 clusters in glass and their effects on the transmittance and crystallization of glass were studied by optimizing the ultraviolet exposure dose and heat treatment conditions. Results indicate that the structure of Ag0 clusters and the precipitation of NaF crystals can be controlled by controlling the ultraviolet exposure dose and heat treatment conditions. Uniform Ag0 clusters and NaF crystals can be obtained when the ultraviolet exposure dose is 4 J/cm2 at 315 nm, the nucleation temperature is 580 ℃, and the crystallization temperature is 650 ℃.

Super-resolution imaging can be achieved by fluorescence emission difference (FED) microscopy through the subtraction of a negative confocal image scanned by a hollow focal spot from a confocal image scanned by a solid focal spot. This study proposes an easily accessible annular pupil filter to enhance the resolution of deformation-free FED imaging. The hollow spot size is reduced by an appropriate annular pupil filter in the light path of hollow spot. Meanwhile, a diaphragm with a high numerical aperture is permitted for the beam of a solid focal spot, and a small solid focal spot which is matching well with the hollow focal spot is achieved. The spatial resolution of FED microscopy is increased under the effects of these two aspects.

Two mechanisms of realizing dual-beam super-resolution optical recording are compared in this paper. One is super-resolution photoinduction-inhibited nanolithography (SPIN), and the other is stimulated emission depletion (STED). We establish a dynamic physical model of STED-based dual-beam super-resolution optical recording technology and study its mechanism in the photo-polymerization process. The differences in dot size and resolution between SPIN-based and STED-based dual-beam super-resolution optical recording technologies are simulated. The results show that the STED-based dual-beam super-resolution optical recording technology has the advantages of no inhibitor and simple principle, however, it needs higher dual-beam intensity and has lower inhibition efficiency of polymerization. In addition, the recording uniformity becomes more unsatisfactory and the dot size increases in the multi-point recording scenario. On the contrary, the SPIN-based dual-beam super-resolution optical recording technology requires much lower dual-beam intensity, and the initiator molecule consumption will cancel out the effect of the inhibitor molecule consumption, leading to great uniformity and stability under multi-point recording. Therefore, the SPIN-based dual-beam super-resolution optical recording technology has better prospect in the field of ultra-high density optical data storage.

By considering the limitations of material selection and shielding effect associated with the manufacturing of diffractive optical elements, this study introduces the fabrication of diffractive optical elements based on the rapid prototyping technology of the ultraviolet (UV)-cured organic-inorganic nanocomposites. Thus, we can obtain diffractive optical elements exhibiting a high refractive index and a high dispersion. Further, a composite formulation suitable for manufacturing diffractive optical elements is obtained based on an experiment on the organic-inorganic nanocomposite preparation. The formulation contains aliphatic polyurethane acrylate (2PUA) with mass fraction of 57.97%, pentaerythritol triacrylate (PETA) with mass fraction of 38.64%, photoinitiator 184 (Irgacure 184) with mass fraction of 1.45%, dispersant 163 (Disperbyk 163) with mass fraction of 1.93%, and ITO nanoparticles with controllable mass fraction. Diffractive optical elements are fabricated using this method. The average microstructural height of the mold-core surface of the diffractive optical elements measured using the step instrument is 13.26 μm. Subsequently, we fabricate the UV-cured diffractive optical elements. Further, the average surface microstructural height of the diffraction optical elements using UV-cured organic-inorganic nanocomposites is 12.58 μm. The relative error between the diffraction optical elements and the mold-core microstructures fabricated by the UV-cured organic-inorganic nanocomposites is 5.141%. The manufacturing technology of diffractive optical elements for the UV-cured organic-inorganic nanocomposites overcomes the limitation of material selection and reduces the occlusion error, making it considerably significant for the rapid prototyping of the refractive-diffractive hybrid optical systems in a wide band.

This study proposes a method to solve the assembly misalignment of two-reverse systems based on the three-level aberration theory in vector wave aberration theory. The proposed method uses the wavefront aberration coefficient of the axial field of view to establish a model for the misalignment solution. Then, the interval error is solved based on the spherical aberration coefficient. The eccentricity and inclination error are solved based on the coma error and astigmatism coefficient, which considerably improves the accuracy and efficiency of the solution. Using a two-reverse optical system as an example, the alignment is simulated based on the Zemax optical design software, the disorder aberration coefficient of axial field of view is reduced to 107 orders of magnitude, the misadjustment error correction is reduced to 105 orders of magnitude, and good alignment effect is achieved. The model is used to guide the alignment of a two-reverse system,so that the calculating precision and the alignment accuracy meet the requirements. The Zemax simulation and practical results demonstrate that the proposed method functions correctly.

In the azimuth transfer system based on magneto-optical modulation, the magnetic field of a magneto-optic material based built-in solenoid driven by alternating current is very important and directly related to the azimuth transmission accuracy. This paper presents the effect of the solenoid paraxial magnetic field driven by alternating current on the azimuth transmission accuracy. First, an electromagnetic field model of a hollow solenoid is constructed using the Maxwell equation, and the influence of the driving signal frequency on the magnetic field is analyzed. Then, a magnetic field model of the built-in solenoid based on magneto-optic material is established according to the ampere loop law. Finally, the effects of a non-relaxation polarization medium, a relaxation polarization medium, and driving signal frequency on the azimuth transmission accuracy are analyzed. The results demonstrate that the driving signal frequency is an important factor affecting the system azimuth transmission accuracy, and the error of the azimuth transmission is regular. The effects of the non-relaxation and relaxation polarization media on the system azimuth transmission accuracy are similar. We expect that these results will provide a reference for further analysis on azimuth transmission accuracy and system optimization design.

The intensity and phase distributions of a Laguerre-Gaussian vortex beam possessing fractional topological charge are simulated in the far-field, and the evolution of these optical properties is discussed when the topological charge changes from fraction to integer. We find that there are two rings with different sizes and shapes in the intensity distribution maps. The brighter petal-like spots occur on the larger rings. There are ellipse-like dark spots with low-intensity in the circumscribed area of the rings. The number of bright spots and dark spots is related to the topological charge of the incident vortex beam.

Due to the change of image feature distribution in target domain, the performance of zero-shot classification for remote sensing scenes degrades. To solve this problem, a zero-shot classification algorithm for remote sensing scenes based on locality preservation is proposed. Firstly, in order to reduce redundant information, the analysis dictionary learning method was exploited to embed the image features and word vectors of the source domain into the common sparse coefficient space, and the sparse coefficients were compulsively aligned for establishing the relationship between the image features and word vectors. Then, the discriminability of sparse coefficients of scene images was enhanced by preserving the local neighborhood relationship among scene images, which is helpful for clustering analysis on the sparse coefficients. Finally, in order to adapt to the change of image feature distribution, the k-means algorithm was utilized to cluster the sparse coefficients of scene images, and the class labels of the initial centers were used as the scene class labels. With the UCM remote sensing scene dataset as the source domain, zero-shot classification experiments were carried out on RSSCN7 scene dataset of the target domain via two type image features, i.e., GoogLeNet and VGGNet. The highest overall accuracies of 50.67% and 53.29% are obtained, which outperform the state-of-the-art algorithms by 8.06% and 9.70%, respectively. The experimental results show that this method can adapt to the feature distribution of remote sensing scenes, and significantly improve the zero-shot classification performance with certain advantages.

Synthetic aperture ladar (SAL) has the characteristics of long imaging distance, high resolution and fast speed, and plays an important role in the field of space-borne imaging. Aiming at the problems of weak return signal, high noise level and poor imaging quality in space-borne SAL imaging, an idea of continuous long-term observation near the intersection point is presented. A mathematical model of space-borne SAL imaging theory is established by using optical heterodyne detection, and the return signal equation and imaging signal-to-noise ratio (SNR) are obtained. The processing flow, image resolution and mathematical simulation of space-borne imaging with different SNR are given. Theoretical analysis and simulation show that when the SNR is high, any sub-data can form a high-resolution image. When the SNR is low, the target sub-image is formed by continuous long-term observation, and the method of combining all sub-images enhances the SNR of the target image and improves the image quality.

The characteristics of the radio-frequency unbalanced Mach-Zehnder interferometer (RF-UMZI) for wavelength demodulation of the fiber Bragg grating (FBG) sensors are studied. The final output power loss of this RF-UMZI due to the incoherent beam loss, insertion loss, and reflection bandwidth of FBG are measured in the experiment. For a certain amount of sample observations of the intensity with a certain microwave frequency, a complete method using the maximum RF intensity discrimination for data processing is proposed. The maximum intensity of each frequency is mapped to obtain the frequency response for notch frequency, and a sensitivity of 0.1692 dB/℃ at 119.96 MHz is obtained. This experiment is of practical reference value in performance improvement and feasibility study for incoherent light and microwave photonics filter utilizing in fiber sensing.

A method for hyperspectral reflectance reconstruction from observed data with an automatic multispectral radiometer is presented. The surface bidirectional reflectance distribution function effect is considered in our method in order to meet the on-orbit calibration requirement of sensors with different spectral characteristics and viewing angles. The satellite-ground synchronous observation data from the National Calibration and Validation Site for High Resolution Remote Sensors are used to validate the proposed method. The results show that the average relative difference between the reconstructed hyperspectral reflectance and the measured reflectance by a field spectrometer is about 2.67%. Compared with observation values of Sentinel-2A/B, the difference is less than 10% for each band. Furthermore, the results of uncertainty analysis show that uncertainty of hyperspectral reflectance obtained by the proposed method is about 3.34%. The overall uncertainty of radiometric calibration at blue, green, red, and near-infrared bands of Sentinel-2A/B is about 3.35%, 3.77%, 4.10%, and 4.29%, respectively.

A multi-channel scanning imaging radiometer is installed on the FY-4 meteorological satellite. To realize high-precision quantitative remote sensing, an on-board calibration device is provided. The device primarily uses a solar diffuser (SD) to reflect sunlight as a standard radiance source, and the solar diffuser reflectance degradation monitoring (SDRDM) device regularly monitors the reflectance variation of the SD. This study introduces the working principle of SDRDM and establishes a calculation model of the bidirectional reflectance distribution function (BRDF) degradation factor of the SD based on the characteristics of on-orbit data. The data show that the SDRDM device is affected by temperature and its uncertainty is 0.165% per ℃. The ratio monitoring method eliminates the influence of temperature. The combined monitoring uncertainties of three channels' degradation factors are calculated, which is 1.48% (k=2) for the first channel and 1.16% (k=2) for the second and third channels, respectively. These results suggest that the SDRDM device can effectively monitor the degradation of the SD's reflectance.

In traditional on-orbit modulation transfer function (MTF) measurements based on periodic targets, there is a known overdependence of the achieved accuracy on the number of target groups. The method introduced in this study aims to overcome such reliance, through a thorough analysis of the principle of the traditional method. We first collect the imaging data of multiple groups of ground periodic targets with certain phase differences and then calculate the output modulation of the imaging system by parametric fitting using all the sampling data as well as the relative phase relations. Subsequently, we compare the input and output modulations to obtain the MTF. We also perform a simulation and a series of experiments of real remote sensing cameras to assess the effectiveness of our method. The results theoretically reveal a small measurement error of less than 0.5% using only two groups of targets, whereas the errors caused by image noise and target-periodic- and measuring-angle matching deviations are less than 4%. This method has good adaptability, and is consistent with the slanted-edge method; therefore, it can be easily applied to on-orbit MTF measurements of high-resolution optical remote sensing cameras.

Herein, the radiation response uniformities of six types of charge-coupled devices and complementary metal-oxide-semiconductor image sensors are studied and compared. Irradiation experiments are performed to investigate the average incremental pixel values and nonuniformities of radiation response signals in different regions of the pixel array. The radiation response uniformities of the global pixel array, regional pixels, and typical pixels in various solid-state image sensors are mainly studied. Results show that the incremental pixel value of the frame image under a steady-state gamma-ray irradiation is not a fixed value, and the uniformity of the radiation response signal in each region of pixel array is not affected by the radiation dose rate. For the same image sensor, the distribution of the radiation response signal in any frame image is the same as the radiation response distribution of any pixel, which is from the pixel array, in the multi-frame image. However, there is a deviation in the statistical results across the typical pixels, regional pixels, and global pixel array due to the difference of the sensor background noise. This study provides a theoretical basis and data support for improving the technology of gamma-ray radiation detection based on image sensors and realizing real-time radiation detection without shading.

Plenoptic camera is a new type of wavefront sensor with large dynamic range and large field of view. However, the linearity of the plenoptic camera and the accuracy of wavefront sensing are low because of the phenomenon of signal saturation,which can be improved by dynamic modulation. The principle and characteristics of plenoptic camera wavefront sensing are analyzed via numerical simulation. The wavefront closed-loop correction effect in dynamic modulation of plenoptic camera is simulated by MATLAB software, and the simulation results of dynamic modulation with plenoptic camera and without plenoptic camera are compared. Simulation results show that, under the dynamic modulation of plenoptic camera, the measurement accuracy is high, the correction effect is good, the strehl ratio of the corrected far-field spot is higher than 0.8, and the performance of the wavefront sensor is better than that of the plenoptic camera without dynamic modulation.

An integrated ultra-light main supporting structure is designed to satisfy the ultra-light, low-power consumption, short-period, and low-cost requirements of a particular micro-nano remote-sensing camera. After comparison with other materials and based on the design requirements, titanium alloy is selected as the research and development focus, and a truss scheme is selected considering mass and power consumption. A mathematical model of topology optimization with fundamental frequency as the objective function is established. In addition, the sensitivity of the objective function is derived, and an improved Heaviside density filter is adopted. As a result, the optimal load path with clear topological results is obtained. Similarly, to obtain the optimal size of each part, a mathematical model of size optimization with fundamental frequency as the objective function is established. Eventually, the mass of the proposed structure is 0.6 kg. The results of finite element analysis and test demonstrate that the integrated main supporting structure can satisfy the tolerance requirement of an optical system and that the fundamental frequency is much higher than the optical load requirement of a satellite platform, which verifies the correctness and rationality of the proposed optimization design.

This study presents an imaging chain simulation based on the camera model under multi-resolution conditions. The structure and directional characteristics of ship target are analyzed under different scales and sampling systems. For a 100-m-long boat, the shape and directional characteristics are stable when the image spatial resolution is >12 m. When the spatial resolution is <12 m, as resolution decreases, identifying the target type and obtaining the target direction using single-frame information become difficult. Compared with single sampling, oversampling can improve the spatial resolution of the image; however, diffusion of the target edge becomes more evident, which degrades the extraction of the target shape characteristics. For a ship target with symmetrical structure, these two sampling systems can equally capture and determine a moving target’s direction.

In this study, we design a plasma refractive index sensor with a cross tie-shaped graphene array structure. Further, the double-resonance transmission phenomenon in the mid-infrared band can be obtained by using the surface plasmon effect produced by the interface between the graphene and dielectric, and the dynamic regulation of the transmission spectrum can be realized by combining the electrically adjustable characteristics of graphenes. Subsequently, the effects of the chemical potential, number of layers, and geometric parameters of graphenes on the double-resonance transmission phenomenon in the structure are studied using the finite-difference time-domain method. The results denote that the resonance position can be tuned by changing the chemical potential and the number of layers of the graphene. Compared with a traditional sensor, this structure exhibits better sensing performance and double-resonance transmission phenomenon after the structural parameter optimization. The sensitivities of two resonance valleys are as high as (1280±24) and (2800±49) nm/RIU with quality factors of 17.1 and 12.3 RIU-1, respectively. These results provide a theoretical basis for the graphene plasma biosensor design.

In this study, surface-enhanced Raman spectroscopy (SERS) combined with two-dimensional correlation spectroscopy is used to develop a quantitative analysis model for rapidly detecting chlorpyrifos pesticide residues in tea. First, using gold colloid as the enhanced substrate, the spectral data of chlorpyrifos residues in tea samples with different concentrations are collected via SERS. Then, the original Raman spectra are pretreated using standard normal variate transformation (SNV). The chlorpyrifos concentration is considered as the disturbance and the characteristic peaks of chlorpyrifos are screened out via two-dimensional correlation synchronous spectrum and autocorrelation spectrum analysis. Parameters of the support vector machine (SVM) algorithm are optimized using the gray wolf algorithm (GWO), and the optimized SVM model is used for analyzing the chlorpyrifos residues in tea. The performance of optimized SVM model is compared to that of the model based on partial least squares (PLS). Results show that 14 chlorpyrifos characteristic peaks are screened using the two-dimensional correlation spectroscopy and the determination coefficient (Rp2) of the proposed SVM model in the prediction set is 0.98, the root mean square error of prediction (RMSEP) is 1.32, and the relative prediction deviation (RPD) is 6.32. These values indicate that the developed model can be used for the actual estimation of chlorpyrifos pesticide residues in tea and performs better than the SVM model based on the 1096-cm1 feature peak and PLS model. Thus, two-dimensional correlation spectroscopy is suitable for screening characteristic peaks related to chlorpyrifos concentrations in tea. This finding leads to a new idea for optimizing the characteristic variables in Raman spectroscopy. Results also show that SERS combined with two-dimensional correlation spectroscopy can rapidly and accurately detect chlorpyrifos pesticide residues in tea. The proposed method will provide methodological support for the development of rapid detection devices for analyzing pesticide residues in tea.

The optical radiation of sapphire during shock compression process is closely related to its transparency and structural phase transition under high pressure. This study investigates the optical radiation characteristics of sapphire above megabar pressure (namely, 100 GPa) on the loading platform of two-stage light-gas gun using the target structure of direct contact between dense metal and sapphire window. A typical optical radiation signal containing metal-interface radiation is obtained using a multi-channel radiation pyrometer. The radiation through sapphire is determined using the radiative transfer model. Results show that the change in radiation temperature of sapphire in the shock-compression region under the pressure above megabar is found to show a significant turning and the shock-induced structural phase transition of sapphire occurs under the pressure near to 87 GPa.