Accuracy of the upward longwave radiation data of GEWEX-SRB (Global Energy and Water Exchanges Project-Surface Radiation Budget), ISCCP-FD (International Satellite Cloud Climatology Project-Flux Data) and CERES-SYN (Clouds and the Earth′s Radiant Energy System-Synoptic Radiative Fluxes and Clouds) in polar regions is studied. In the experiment, two kinds of ground observation data of BSRN (Baseline Surface Radiation Network) and CEOP (Coordinated Energy and Water Cycle Observations Project) in polar regions are used as reference data, and the downscaling method is used to deal with them. Finally, accuracy of the radiation products is evaluated. Research results show that the overall accuracies of the three kinds of commonly used upward longwave radiation data are lower in polar regions. Absolute values of the root mean square error (RMSE) and the mean absolute error (MAE) are more than 15 W·m-2. The mean RMSEs of GEWEX-SRB, ISCCP-FD and CERES-SYN are 23.70 W·m-2 (8.69%), 25.14 W·m-2 (9.62%) and 22.98 W·m-2 (8.80%), respectively, and the mean MAEs are 18.53 W·m2 (6.96%), 20.09 W·m2 (7.70%), and 17.73 W·m2 (6.79%), respectively. Through the analysis of accuracy, the factors that affect the accuracy of the upward longwave radiation products include spatial heterogeneity, input parameter errors, cloud influence and low spatial resolution of radiation products and so on.

A novel framing camera based on multiple magnetic focusing imaging and electron pulse time dilation is developed. The relationship between the spatial resolution and the number of the magnetic focusing lenses as well as that between the spatial resolution and the current is investigated. The experimental results show that the spatial resolution is the best when three magnetic focusing lenses and the suitable current are chosen. The larger the off-axis distance is, the worse the spatial resolution is. The relationship between spatial resolution and bias voltage is investigated and it is found that the spatial resolution improves with the increase of the bias voltage between the photo-cathode and the mesh. The image plane of this novel framing camera is a curved surface and the whole cathode surface cannot be simultaneously imaged. The temporal resolution is improved to 11 ps when the time dilation technology is introduced and the static spatial resolution is 5 lp·mm-1 when the image ratio is 2∶1.

With high technology development and its extensive application in the military, the modern infrared reconnaissance capability has been continuously improved, which also promotes the development of infrared camouflage capability. For the imperfect index system of the air defense missile infrared camouflage capability and the difficulty in quantitative evaluation, a comprehensive index system is proposed. We analyze the air defense missile infrared camouflage capability from the three aspects of infrared reconnaissance capability, infrared implicit capability, and infrared false capability. The evaluation of air defense missile infrared camouflage capability is conducted by the set pair analysis model based on the comprehensive weighting method, and the method is verified through an example. The analysis results show that the construction direction of the air defense missile infrared camouflage capability is all-directional, multi-band, and systematic.

Moiré fringe expressions in many cases are analyzed and verified via simulation based on the shadow shading and spectrum analysis principles. The influence laws of the center distance of two gratings and the number of the intersection points for bright fringes on the patterns of the families of hyperbolic and elliptic moiré fringes are obtained. The research results show that the family of hyperbolic moiré fringes has more advantages on discrimination and measurement than that of elliptic moiré fringes. Based on the transmittance function of concentric-circle gratings and the computer-generated hologram, the moiré fringes of this concentric-circle grating can be generated by the use of spatial light modulator. With magnification and the suitable low-pass filter, the hyperbolic moiré fringes widely used in engineering are obtained.

We derive the coefficient equation for the first-order orbital angular momentum-polarization mode dispersion (OAM-PMD) of OAM mode in a ring fiber by using the OAM-PMD dynamic equation and the fixed birefringence cascaded model. We also numerically calculate the influences of geometrical birefringence on the effective refractive index difference between the odd and even modes that constitute the OAM mode and calculate the variation of first-order OAM-PMD coefficient with the angular frequency under different ellipticities of ring fibers. The results show that the first-order OAM-PMD coefficient is determined not just by the effective refractive index difference between the odd and even modes that constitute the OAM mode, but also by its variation with the angular frequency. We find that the ellipticity of the ring fiber increases the first-order OAM-PMD coefficient, particularly for relative lower-order OAM modes, and thus severely limit the property and propagation distance of the OAM modes.

In order to meet the need of large strain range measurement on the key structures of ship, bridge, aircraft, and so on, we design a multi-loop desensitized fiber Bragg grating (FBG) strain sensor based on low temperature plasma. Finite element analysis of a tricyclic desensitized strain gauge substrate with a length of 30 mm is carried out with a displacement of 0.083 mm on each of the left and right end faces. After calculation, the strain in the gate region is about 1700 με and the desensitization coefficient of the structure is 2.91. Two contrast groups are adopted to verify the sensing characteristics within +5000 με; low temperature plasma is used to treat the gate region surface for one group sensor; while the other is set as default. The results show that the more times the plasma discharge treates the gate region surface, the larger the fiber optical power becomes. The average measurement error of the system is about 50 με, and the full-scale accuracy is less than 0.5%, which solves the problems of instability and poor linearity of the system calibration results caused by the pollution of the gate end face during the packaging process.

Using the Monte Carlo method, we investigate the transmission characteristics of light beam through seawater for long-reach undersea wireless optical communication system. The traditional Gaussian beam is replaced with flat-topped beam, which can extend the distance of communication system. Then we compare the transmission characteristics of flat-topped beam and Gaussian beam in three kinds of clear seawater, and simulate the two kinds of underwater wireless optical communication systems based on pulse position modulation. The results show that the upper limit of reliable video transmission distance of undersea wireless optical communication system is 268 m for using Gaussian beam and 340 m for using flat-topped beam under the same condition, respectively. The application of flat-topped beam is viable to extend the communication distance of underwater wireless optical communication system in clear seawater. The results provide a reference for the design of long-reach underwater wireless optical communication systems.

A new type of photonic crystal fiber with elliptical air holes in the center is designed, and we study the properties including electric field distribution, birefringence, dispersion, nonlinearity, and confinement loss of fundamental mode of this fiber by using full vector finite element method. The results show that the electric field energy is bound in the fiber core. The birefringence can be reached 5.958×10-2, which reaches the magnitude of 10-2 at a wavelength of 1.55 μm. In the wavelength range from 1.50 μm to 1.60 μm, the dispersion is (-549.2±5) ps/(nm·km), which is a highly flattened negative dispersion. The nonlinear coefficient in x-polarization of this fiber is 46.82 W-1·km-1, and the low confinement loss is 5.413×10-4 dB/km at 1.55 μm, and the confinement losses of the polarization states in the y direction are 6423 times than those in the x direction. The proposed photonic crystal fiber has the characteristic of high birefringence, high nonlinearity, highly flattened negative dispersion, and low confinement loss, which could be widely used in the field of optical fiber sensing, polarization control, dispersion compensation, nonlinear optics and so on.

A fiber sensor which can measure the temperature and refractive index simultaneously is fabricated based on an all-fiber Mach-Zehnder interferometer (MZI). This MZI is formed when a section of a hard plastic cladding fiber (HPCF) is spliced between two sections of single-mode fiber (SMF). Because of mismatching of the core diameters of SMF and HPCF, interference spectrum is generated by the transmission light from the HPCF. As the interference spectrum varies with the change of ambient temperature and refractive index, the simultaneous measurement of temperature and refractive index is realized. Experimental results show that the sensitivity of temperature and refractive index can achieve to 13.3 pm·℃-1 and 52.56 nm·(RIU)-1, respectively. This optical fiber sensor has the characteristics of small volume, simple structure, easy to fabrication and high sensitivity, which is suitable to operate in electrical noisy surroundings.

Health monitoring of the high-voltage transmission line system with the length of 4 km is analyzed by means of fiber Bragg grating (FBG), phase sensitive optical time-domain reflectometer (Φ-OTDR) and distributed temperature sensor (DTS) based on Raman scattering. The strain and temperature of the transmission tower and the transmission wire are focused on during the transmission line galloping.104 FBGs, working as strain and temperature sensors, are installed on one of the power towers. Based on the communication fibers in the optical fiber composite over-head ground wire(OPGW), Φ-OTDR and DTS technologies are used to monitor the galloping of the transmission line. These three kinds of optical fiber sensing schemes are complementary to each other and the health monitoring of the power transmission system is realized.

According to the similarity of information in Brillouin optical time-domain analysis (BOTDA) sensing image in spatial domain, Kuwahara filtering method for sensing image denoising is proposed. The central element value can be restored according to the correlation among adjacent pixels in filtering window. The results show that the window size of Kuwahara filter should approach to the theoretical value of spatial resolution. The proposed method can make an average signal noise ratio (SNR) improvement of 6.7 dB and Brillouin frequency shift (BFS) error decrease of 0.58 MHz for BOTDA sensing images in different SNRs, without distorting spatial resolution. The method improves the performance of the sensor without increasing the BOTDA sensor hardware, so it has the potential application to high-resolution, long distance sensing and the other types of distributed optical fiber sensors.

The application background and techniques to generate sawtooth wave based on photonic approaches are introduced. To overcome the electronic bottleneck of electronic waveform generation methods, we propose a novel method to generate sawtooth waveforms by using two parallel Mach-Zehnder modulators (MZMs) based on external modulation. We adjust the voltage of the direct current source and the intensity of the radio frequency source in order to make MZMs to operate under conditions of quadrature transmission point (QTP) and proper modulation index. Thus, the frequency components′characteristics of the photocurrent from optoelectronic balance diode are coincident with the Fourier series of sawtooth. A mathematical model is built, and the scheme is verified experimentally. The root mean square error is used to evaluate the simulated and experimental results. In addition. The influences of the extinction ratio and the drift voltage on the output signal are analyzed. The results show that the proposed system is flexible and has strong scalability. The waveform generation and slope switching can be realized through simple actions.

In order to meet the requirements of modern intelligent equipment and infrared interactive identification, we design a miniature infrared wide-angle lens by CodeV and Zemax optical design software. The lens is equipped with three plastic lenses and one infrared band pass filter. Its optical structure is negative-positive-positive. The design results show that F number is 2.2, the maximum viewing angle is 129° and the mechanical total length is 3.8 mm. Modulation transfer function (MTF) value of all fields is larger than 0.5 at 1/2 Nyquist frequency. The assembled lens is tested to show that MTF performance meets design requirements and the infrared detection function can be achieved.

With the development of the image content, screen content (SC) images generated by computers begin to spread. In order to code the screen content more efficiently, a new tool named palette mode is added into the High Efficiency Video Coding (HEVC) to improve the compression performance, but it will greatly increase the computational complexity and coding time. We propose an adaptive palette mode decision algorithm based on the complexity analysis of the video content. The proposed algorithm divides the luminance component of the image into blocks and applies discrete cosine transform (DCT) to measure the complexity of each block. Then a judge matrix is derived based on the complexity values. Finally, the coding unit information and the judge matrices are used to judge whether to enable or disable the palette mode. According to the experimental results, compared with the anchor encoder that enables the palette mode, the total encoding time saving of the proposed algorithm can reach 69.24% of the total encoding time saving when the palette mode is disabled, with averagely 0.33% of the bjntegaard delta bit rate (BDBR) increase and 0.03 dB of the bjntegaard delta peak signal-to-noise ratio (BDPSNR) decrease.

Image memorability prediction involves two problems, feature representation and prediction model. Most of previous researches just focused on addressing the first problem by investigating the factors making an image memorable, and conducted feature fusion and regression learning in two separate steps. Results of feature fusion decide the performance of regression. Lack of using an integrated learning mechanism cannot efficiently address image memorability prediction tasks, since it may lead to sub-optimal prediction results. To solve the problem presented above, we introduce a novel image memorability prediction model based on low-rank representation learning. We seek the lowest-rank representation among all the samples by projecting the original feature matrix into a subspace spanned by a low-rank projection matrix. Meanwhile, we learn a regression coefficient to build connections between latent low-rank representations and memorability scores by linear regression. Furthermore, we develop an effective algorithm based on the augmented Lagrange multiplier method to solve our model. Extensive experiments conducted on publicly available image memorability datasets demonstrate the effectiveness of the proposed schemes.

Tensor decomposition is a powerful computational tool for analyzing multi-dimensional data. The traditional Tucker decomposition models are generally proposed based on the isotropy hypothesis, meaning that the factor matrices are learned in an equivalent way for all modes (such as orthogonal or non-negative constraints), which is not suitable for the heterogeneous tensor data. We propose a low-rank regularized heterogeneous tensor decomposition (LRRHTD) model for subspace clustering. The core idea of LRRHTD is that we seek a set of orthogonal factor matrices for all but the last mode to map the high-dimensional tensor into a low-dimensional latent subspace. In the meantime, we seek the lowest-rank representation of the original tensor by imposing a low-rank constraint on the last mode, in order to reveal the global structure of samples for the purpose of clustering. We also develop an effective optimization algorithm based on augmented Lagrangian multiplier to solve our proposed model. Experiments on two public datasets demonstrate that the proposed method reaches convergence within a small number of iterations and achieves promising clustering results in comparison with state-of-the-art methods.

Aiming at the problems of feature sparseness and noise sensitivity when the temporal-spatial local direction angle mode is applied to the video emotion recognition, we propose a new feature extraction algorithm, the spatiotemporal local ternary orientation pattern (SLTOP). Considering the complementarity of facial expression and posture characteristics in recognition, a classification method based on the cloud weighted decision fusion is proposed. The video image is preprocessed to obtain the sequence of the two modes of facial expression and gesture. For reducing the sparseness of the feature histogram, we extract the SLTOP feature of the sequences of expression and posture, learning from the idea of gray level co-occurrence matrix. In the stage of decision fusion, the cloud model is introduced to implement the cloud weighted decision fusion for the two modes of expression and posture making to realize the final recognition of dual-modal emotion. The average recognition rate of the single modal of facial expression and body posture in the FABO database is 92.21% and 96.76%, respectively. And they are approximately 18.42%, 22.01% and 9.15% higher in expression, respectively, when compared with the volume local binary mode, local binary mode three orthogonal planes (LBP-TOP) and temporal-spatial local ternary pattern moment (TSLTPM). In the single-posture modal, they are 26.59%, 29.53%, 1.98% higher, respectively. The average recognition rate obtained by cloud-weighted fusion is 97.54%, which is higher than that of other experiments. The proposed SLTOP has good robustness to the noise and illumination. The weighted decision fusion method of cloud model is used to greatly express the performance of two classifiers with expression and posture. The superiority of the recognition results in this paper is shown comparing with other classification methods.

The classical total variation image inpainting algorithm costs more iterations and time to remove the text and scratches. Aiming at this problem, we propose an improved algorithm. Firstly, the diffusion accommodation coefficient is added into the regularization term. Secondly, a self-adaptive parameter that varies with the number of iterations is added to the diffusion accommodation coefficient. Thus, the algorithm diffuses at a faster speed in the early iteration and slows down in the later iteration, and the restored image maintains a sharp edge. A large number of simulations show that the improved algorithm reduces the number of iterations and running time in the scratch and text removal, and the restored image has good visual effect.

The point cloud scanned by terrestrial laser scanning contains mass data. Not all of these data are useful in the process of application, especially for the building point cloud, the building can be described when the building profile is determined. Therefore, the geometrical characteristics of adjacent points are used to extract features of the building point cloud. Firstly, the proposed algorithm uses the k-nearest neighbor search algorithm to search the adjacent points of one point. The normal vector and datum plane are determined according to the adjacent points. The characteristics of normal vector angle between the probe points and the adjacent points are used to determine the building boundary. Secondly, the total least squares and weighted principal component analysis are used to improve the random sample consensus algorithm. The point clouds on both sides of the fold boundary are determined by the improved algorithm. The characteristics of boundary are used to probe the building fold edge. The results show that the proposed algorithm is fast and less redundancy, and can be used to extract feature lines of the building with more than 90% eliminating rate of the invalid point cloud.

Aiming at the problem of artifacts in the convergence of object edges in multi-focus images fusion, a multi-focus images fusion algorithm is proposed based on non-subsampled Contourlet transform(NSCT) and guided filtering, by which the multi-focus images are decomposed. For the sub-band coefficients of low-frequency, an edge-based weighted fusion scheme is adopted, while, for sub-band coefficients of band-pass directional, bidirectional Laplacian filtering is utilized to extract edge and significant information. Meanwhile, the guided filter is used to correct initial fusion weigh, and NSCT reconstruction is performed to obtain fused multi-focus image. The experimental results show that, compared with seven other fusion algorithms, the proposed algorithm can improve richness and clarity of fusion image, avoid artifacts at objects edge, and improve the fused image′s general quality.

The blurring of images creates great inconvenience in the process of recognizing and analyzing the content of images. For overcoming this problem, an efficient deblurring algorithm is proposed. In order to improve the efficiency of deblurring algorithms, we propose a model based on variational method for deblurring of color images. The nonlinear diffusion equation is used as the regularization term in the variational energy equation. In addition, the single channel is extended to multi channel in the process of dealing image and the split Bregman method is also introduced in the final phase of image restoration. The debluring effct of the proposed algorithm based on nonliner diffusion terms has better capability of smoothing filtering and preserving image edge information, faster calculate time, and higher restoration image quality than other algorithms. The experiments have verified the effectiveness of the proposed method. The deblurring algorithm based on nonlinear diffusion term improves the efficiency of image restoration, and has good visual evaluation and objective evaluation results.

Underwater imaging technology is one of the research hotspots in underwater exploration. According to the current problems of underwater imaging devices, a new target imaging and processing system is proposed. The imaging scheme, imaging principle, imaging analysis and processing algorithm are studied. Firstly, theoretical analysis and numerical simulation are carried out based on the Fresnel 's law. Specifically, the MATLAB software is used to simulate the reflection polarization characteristics, and the amplitude ratio and phase difference of two vertical components in reflected light are obtained. Secondly, in the case of liner polarized laser illumination, based on the Stokes imaging theory, the polarization information of the object is detected, and the Stokes parameters of the object are obtained. Finally, the polarization degree and polarization angle images are obtained and analyzed after being converted into HSV space and Lab space. The results show that the polarization degree and polarization angle images can highlight the material information, improve the contrast of different materials and make it more easier to be recognized by human eyes.

The phase modulation method forms a latent image by displacing the local dot to achieve anti-counterfeiting purposes, but the changes of the spatial position would affect the color rendering. The influence mechanism of the hidden image on the color attribute is analyzed by exploring the changes in the spatial distribution. Based on the minimum position transformation and center position transformation model in phase modulation, the local variation caused by dot displacement is quantified, and the influence of dot distribution and density on dot color rendering are analyzed. The results show that the phase modulation latent image method resets the location of dots, and the color attributes of different dot distributions and density change accordingly, which affects the image color rendering. Therefore, the rationalized phase modulation scheme is a powerful guarantee for the color reproduction, and can provide a valuable theoretical basis for the study of anti-counterfeit image quality.

To overcome the problem of poor recognition of traditional face recognition algorithms in single sample environment, a single sample face recognition algorithm combining improved center-symmetric local binary pattern and bit-plane decomposition (ICSDBP) is proposed. Firstly, the texture feature of a face image is extracted by the improved center-symmetric local binary pattern operator to obtain two texture feature images with different radii, and then each texture feature image is decomposed into 4 bit-plane images. Finally, eight feature images are combined in series, and the nearest neighbor classifier is used for classification and recognition. The simulation results on the AR, CAS-PEAL and Extend Yale B face databases show that the proposed algorithm has high recognition rate and high recognition speed, and it is robust to the variations of face illumination and face expression.

Aiming at the key point description and repeatability in the method of key point detection of three-dimensional (3D) point cloud is not strong, and the number of detected key points is small, we propose a novel algorithm of key point detection. Firstly, in order to improve the efficiency of the algorithm, the uniform sampling method is used to reduce the number of points in the 3D point cloud that can reduce the complexity of the 3D point cloud. Then, we use Signature of Histograms of OrienTations (SHOT) descriptor to describe the points uniformly sampled in multi-scale, and analyze the uniqueness of the multi-scale SHOT descriptors at each point, and select the SHOT descriptor with larger discreteness of points as the key points. The proposed method uses the descriptive SHOT descriptor to describe the neighborhood of the key points, and enhances the descriptivity of the key points. The experimental results show that the uniform sampling is highly efficient in time and meets the time requirements of the keypoint detection. The proposed method has better reproducibility than Harris 3D, scale invariant feature transform (SIFT) and internal shape signature (ISS) key point detection algorithms in the key point detection. Therefore, the proposed method can detect high quality key points in the 3D point cloud model and scene effectively and quickly.

In order to solve the problem of low spatial resolution of hyperspectral image, a method based on spatial spectral joint sparse representation is designed. Firstly, we extract the different reflectance spectra of scenes and obtain a spectral dictionary with strong sparsity and weak coherence by exploiting compressed sensing dictionary learning algorithm. Then using sparsity, non-negativity and spatial structure similarity of hyperspectral image signals, we obtain the sparse coding matrix from the high-spatial resolution low-spectral image of the same scene by the simultaneous orthogonal matching pursuit algorithm. Finally, we combine the spectral dictionary with sparse coding matrix to get the target image. As a result of the combined spatial and spectral information, the simulated data and real data experimental results show that this method can effectively reconstruct image detail information and texture structure compared with bicubic interpolation method and matrix decomposition method, and effectively improve the value of average peak signal-to-noise ratio, average structural similarity, and spectral angel mapper, and maintain the spectral information better.

Aiming at the good performance in computer vision for depth learning, a multi-focus image fusion algorithm based on depth learning is proposed. Based on the existing AlexNet network model, the convolution kernel size and step size are improved. The focused image blocks and the defocused image block are classified by using the improved scoring mechanism of deep learning network. Then, the correction matrix is used to correct the misjudgment image blocks. The boundary zone of image focus and defocus is subdivided and repaired. Six pairs of multi-focus images are randomly selected to verify the effectiveness of the proposed method. The experimental results show that, compared with other algorithms, the fusion results obtained by this algorithm can preserve the original high-frequency information of the image, and achieve good performance on four evaluation indexes of mutual information, edge information retention, entropy and average gradient.

In order to assess the quality of distorted videos accurately without reference videos, a universal no-reference video quality assessment algorithm is proposed, which applies three-dimensional (3D) convolutional neural networks to extracting spatiotemporal features of distorted videos. Firstly, the convolutional neural network model 3D ConvNets is trained on the video quality database, and then the features related to video distortion degree are learned. Then, 3D ConvNets is used to extract features of the input distorted video, after which L2-normalization and principal component analysis are performed to prevent overfitting and eliminate redundancy. Finally, linear support vector regression is used to predict quality score of the distorted video based on video quality features. The experimental results show that the proposed algorithm can assess video quality accurately across different kinds of distortion, and it still maintains a high level of accuracy when the test video database is changed. Last but not least, the computational complexity of quality assessment process is extremely low for the proposed algorithm.

A Fourier ptychographic microscopy is proposed based on a rotating arc-shaped array of LEDs for illumination. Large-angle illuminations can be achieved and the problem of non-uniform illuminations can also be solved. The advantage of the proposed approach is validated by an experiment comparing the planar LED matrix with the rotating arc-shaped array of LEDs.

As an effective means of computational imaging, focal sweep imaging model can extend the depth of field. Based on the ambiguity function theory, we propose an inverse filtering computational imaging model based on focal sweep mode and analyze the expand performance of the depth of field. We obtain the optical transfer function of focal sweep imaging using focus error based on the relationship between the ambiguity function and the optical transfer function. A theoretical analysis of the approximate three-dimensional space invariance of the optical transfer function is given. Based on the optical transfer function, we establish an inverse filtering computational imaging model of focal sweep. Taking a concrete imaging model as an example, we analyze the influence of different scanning ranges on the expand performance of depth of field of focal sweep imaging model based on the HOPKINS criterion. Through numerical simulation, we verify the correctness of the optical transfer function of focal sweep imaging model. We analyze and compare the imaging results of focal sweep imaging model of different scanning ranges (0.09, 0.18, 0.36 mm) based on inverse filtering model. The analysis shows that the depth of field can be extended by focal sweep imaging model; the larger the sweep distance, the better the performance of the depth of field of focal sweep imaging model.

A prototype based on the tip-tilt mirror correction system is designed to obtain higher quality observation data and improve the efficiency of the telescope, which is used for the research on improving closed-loop tracking precision of the 2.4-meter telescope in Lijiang. This paper introduces the development of the prototype and carried out the actual test in the 2.4-meter telescope. The results show that the system can realize the correction frequency of 245 Hz, and the closed-loop tracking precision of the telescope is improved by 7.3 times. Meanwhile, the coupling efficiency of the high resolution echelle spectrograph is improved by 28.6%, the imaging quality of the fast photometry system is improved obviously. The system can meet the requirements of astronomical observation.

Based on the principle of pulse ranging, we obtain bridge point cloud data by 3D laser scanner at different cases, and acquire deformation information of key components in this bridge by qualitative and quantitative analyses of point cloud data. In this paper, a new method based on target point cloud is proposed to get precise deformation of key components by fitting the center coordinate through the outline point cloud of circular target. The calculated results are compared with the results of the displacement transducer measurement and the finite element model (FEM) analysis. Comparison results show that the proposed method combined with the bridge deformation data acquired by point cloud has higher accuracy, and it avoids the disadvantage of single point cloud measurement that cannot get the overall deformation of the structure.

Measuring the rotating velocity of the wheel with machine vision is efficient and straightforward. Measuring the high-speed rotation with a high-speed camera can generate massive data. In order to reduce the massive data, we propose a method to measure the relative high-speed rotation of the wheel by a low-speed electronic rolling shutter camera. This method bases on that the effect of rolling shutter can induce geometric distortion in the image when the wheel is rotating fast. The information in the distortion image can be used to get the rotating velocity of the wheel, and the purpose of measuring relative high-speed rotation with low-speed camera is realized at the same time. The proposed algorithm is validated in a simulation model which reveals the relationship between the rotation and the distortion image. In order to eliminate the dualistic caused by the spatial wheel photographed by a single camera, the rotation property of the wheel is researched. Finally, the verification experiment is carried out. The result of the experiment shows that this method can detect the rotating velocity which is higher than the speed of the camera, and the relative error is less than 4%.

As for the problem of long machining and measurement iteration cycle of metal reflectors by the single point diamond turning, the fringe reflection method with a large dynamic range and fast detection speed is introduced, and the on-machine surface measurement of metal reflectors is realized, which improves the manufacturing efficiency. The mechanism of surface shape measurement based on fringe reflection is investigated. By the ray tracing program, the simulation is conducted as for the reflector surface with an aperture of 100 mm and the micron-sized requirement of position calibration in the fringe reflection on-machine surface shape measurement system is analyzed. The on-machine measurement of concave spherical metal reflectors with an aperture of 100 mm is carried out, and the measurement precision is superior to 1 μm. This research provides a certain reference for the machining of reflector by the single point diamond turning.

To tackle the problem that the camera-based beam analyzer often gives the different results of the laser beam quality, we analyze the impact of the relevant parameters on the measurement error of the laser beam. The beam diameter is calculated by the ISO 11146 standard based on the Gaussian model with the noise level corresponding to the real one. According to the actual operation during testing, four parameters are analyzed, including the light intensity saturation, integral area ratio, signal to noise ratio and actual beam size. Compared with the prior works, we found the key trend of the camera parameters on the measurement error and the correlation between the parameters, which will be helpful to put forward more specific requirements on how to choose the camera and how to set the integration time and the calculation area.

It is difficult for path planning of processing and the cladding accuracy is susceptible when the damaged area repaired by laser cladding is a free-form curved surface with an obvious curvature change. As for the above problem, a method of regionalization of the fast generated trajectory point set according to feature type is proposed. The joint angle of robot arm has a little change when working in the same area. The track points in the adjacent area are adjusted to meet the requirement of cladding quality under the coordination of the positioner. The operation model of robot and positioner is established and the aim of their coordination is obtained. The precision requirement of laser processing is met and the efficiency of robot repair of curved parts is improved.

Fiber laser is widely used in many fields, such as optical fiber communication, optical fiber sensing, spectrum measurement and so on. A broadband continuous tunable erbium-doped fiber laser with multiple output ports is designed and fabricated based on a digital micromirror device (DMD) and widely tunable optical filter. The characteristics of the laser are theoretically simulated and analyzed using a traveling-wave rate-equation model. Based on the theoretical results, an experimental system of the broadband tunable fiber laser with eight output ports is built. The experimental results show that the output wavelength range for each output port is 50 nm, which covers the whole C band and extends to S and L bands. The pumping threshold power is 17 mW, the 3 dB linewidth of the output laser is less than 0.02 nm, and the side mode suppression ratio is greater than 50 dB in the whole band. The stability of the laser output is measured within 100 min. The results show that the power fluctuation is less than 0.4 dB, and the wavelength jitter is less than 0.02 nm.

The 1Cr15Ni4Mo3 alloy powder is cladded on the surface of 30CrMnSiNi2A ultra-high strength steel by the laser cladding technique. The microstructure and mechanical properties of the cladding layers are investigated. The results show that, the microstructure is mainly the martensite and austenite double-phase structure. For the cladding joints, after the low-temperature tempering at 200 ℃, the tensile strength is larger than 1300 MPa, the extension rate is 8.1%, and the impact toughness is 53.8 J·cm-2. The tensile strength and extension rate reach to 90% of those of 30CrMnSiNi2A ultra-high strength base steel, while the impact toughness is doubled if compared with that of base material.

By the fatigue crack growth experiment, the effect of laser shock processing (LSP) on fatigue crack growth rate of TC4 repaired parts is investigated and the changes of surface residual stress, surface roughness and fracture morphology of TC4 repaired parts before and after LSP are compared and analyzed. The experimental results indicate that, the laser repaired zone of TC4 repaired parts is composed of β grains and α phase which distributes along the grain boundaries, and the heat affected zone consists of equiaxed α grains and β transformation structure. After the LSP, the full width at half maximum of diffraction peaks is larger, the surface residual stress is compressive stress, and the surface roughness increases. Based on the modified seven-point incremental polynomial fitting method, the fatigue crack growth rate equations of different repaired parts are obtained. The fatigue crack growth rate of TC4 repaired parts with LSP is smaller than that without LSP.

Characteristics of the temporal point spread functions (TPSFs) of chaotic laser through intralipid solution are experimentally studied. Based on the delta function characteristic of the correlation function of chaotic signal, we retrieve TPSFs of the measured system with chaotic laser as light source by correlating the detected signal with the original signal. The scattering coefficient is increased by increasing the concentration of intralipid solution. While the absorption coefficient maintains unchanged, TPSFs of the intralipid solution at different concentrations are experimentally measured and the differential path-length factors (DPFs) are extracted from the TPSFs of intralipid solution, which can qualitatively reflect the optical properties of the intralipid solution. Results show that degree of the correlation between the two signals is decreasing with the increasing concentration of intralipid solution, and DPFs are positive correlation with the scattering coefficient of intralipid solution.

In order to meet the developing demands of subsequent larger scale amplifier and improve the field installation quality of the optomechanical modules of existing amplifier, we analyze the flaws in the structure design of the field installation process device, study the technique flow, accuracy and time-allotment of field installation, construct the function structure tree of the field installation device, and optimize the sub-function and structure integration. Based on these studies, the design sketch of the new field installation device is proposed, which is suitable for the optomechanical modules installation of existing amplifier. In the following, realization process and advantages of the system are further analyzed, the theoretical calculation of key structure, engineering design, sub-functional verification and machine debugging of the new device are carried out before it is used to verify design effectiveness through batch installation mission test of optomechanical modules of existing amplifier. The results show that the new device meets the requirements of the field installation of optomechanical modules of amplifier, the feasibility of its structural design is verfied.

Rod amplifier with non-imaging reflector is designed based on the edge-ray principle. Under the same flashlamp electrical power and rod dimensions, the stored energy density and the small-signal gain coefficient of Nd∶glass rod amplifier with non-imaging and imaging reflector are simulated, respectively. The numerical simulated results are consistent with the experimental results. The non-imaging reflector can reflect all the xenon flashlamp rays to the Nd∶glass rod surface, which can enhance the photoelectric conversion efficiency, reduce the generation of waste heat, increase the pumping efficiency and the amplifier′s gain property. This design can achieve considerable cost savings and improve the efficiency of the amplifier.

Aiming at the problems of slow speed, high rates of false detection and miss detection in denim artificial operation, we propose an automatic defect detection algorithm of denim by using the optimal Gabor filter. Firstly, an arbitrary two-dimensional Gabor filter is constructed for the normal denim image. Meanwhile an improved differential evolution algorithm is used to optimize the parameters of Gabor filter to get the best match with the normal denim texture. Secondly, the Gabor filter is constructed according to the optimal parameters, following which, an operation of convolution is applied to the image to be detected to obtain the corresponding feature image. Then, the initial detection result is obtained by combination with the threshold operation. Finally, we use the rectangular box and the local Otsu method to separate the exact defect area. Experimental results show that the proposed algorithm can better detect the denim defects with short learning time, strong robustness and high accuracy.

In facial expression recognition, the traditional machine learning methods based on the manual feature extraction are time-consuming and less robust. The current convolution neural networks relying on single channel convolution kernel are not sufficient to extract feature, which makes the recognition rates low. We propose a multi-resolution feature fusion convolution neural network, which is combined with two uncorrelated and channels with different depths to extract multi-resolution features. After fusing the two channels feature, a softmax classification is used to classify the facial expression. The experiments on JAFFE and CK+ facial expression databases show that compared with traditional machine learning methods and existing convolution neural networks, the proposed convolution neural network structure model has the advantages of good robustness, strong generalization ability, and fast convergence speed.

The effect of gold nanoparticles on the fluorescence spontaneous emission of CdSe/ZnS quantum dots (QDs) is investigated based on the time-correlated single photon counting technique. The quantum dot samples coupled with gold nanoparticles effectively are prepared. The fluorescence lifetime of QDs with a high concentration is measured, and it is found that the fluorescence lifetime of QDs can be significantly reduced by the gold nanoparticles. The fluorescence properties of a single QD are also studied and it is found that the fluorescence lifetime of the quantum dot coupled with gold nanoparticles is reduced to about one percent of that without gold nanoparticles. The effects of the polarization direction of QDs, the distance between the QDs and the gold nanoparticles, the diameters of gold nanoparticles and other parameters on the fluorescence spontaneous emission rate of QDs are investigated by the numerical calculation.

The electric-field control of resistance and magneto-optical Kerr effect of all-solid-state Au/Ti/Y2CeFe5O12 multilayer structure is realized at room temperature. At 635 nm wavelength, the rangeability of saturation magneto-optical Kerr rotation angle is 58.1 μrad under the operation voltage of 1.5 V. The corresponding energy dissipation is 0.66 nJ·μm-2 and the response time is 300 s. Moreover, the control is reversible and non-volatile. The critical effect of Ti layer on such a modulation is disclosed by contrast to Au/Y2CeFe5O12. The occurrence of oxygen ion migration is confirmed via the characterization for the change of electrical resistance of multilayer structure under the effect of electric field. The oxygen ion migration is the mechanism of electric-field control of magneto-optical effect. This prototype device offers a new way to develop electric-field tunable magneto-optical devices.Key words

In order to explore the rule of optical properties of ZnO changing with the concentration of solution, nano-ZnO with hexagonal wurtzite structure is synthesized by hydrothermal method at low temperature. Then, the morphology, structure and optical properties of the samples are characterized, respectively. The results indicate that nano-ZnO grows preferentially along the (002) plane. And complex of Zn (OH) 2-4 is the growth element of nano-ZnO. The morphology of the samples is influenced by the concentration, temperature and reaction time of the solution. As the concentration ratio of OH- and Zn2+ increases, the sample changes from the rod-like structure to the flaky form, and the phenomenon of reunion appears. Photoluminescence (PL) spectra shows that the sample has fine emission ability in red to green band, and it has not only an obvious visible emission band near the wavelength of 560 nm, but also a ultraviolet emission peak near 374 nm. Finally, the luminescence mechanism of the sample is discussed.

Endoscopic objectives are key components of two-photon imaging used in medical endoscopy imaging. The imaging quality and signal light collection efficiency are crucial to the final image quality. An objective lens with high collection efficiency, 400 μm field of view, and compact structure is designed for the optical fiber scanning two-photon imaging system. In this system, a 920 nm femtosecond laser emerges from a double cladding fiber and excites the sample after the objective lens. The excited 460 nm second harmonic signal and 510 nm fluorescence are collected into the fiber cladding through the objective lens. In order to improve the collection efficiency during this process, we design the axial chromatic aberration of the objective so that more signal light enters the cladding. The design of the system is optimized by Zemax software. The results show that the modulation transfer function in the whole field of the objective at 920 nm is larger than 0.25 at 700 lp/mm, which meet the requirements of the system. Meanwhile, the signal light collection efficiency of the objective lens designed in the non-sequential mode and the traditional gradient index lens is compared. The simulation results show that the signal light collection efficiency of this objective lens is 54%, which is two times higher than that of the traditional gradient index lens.

There are two kinds of nonlinear optical distortion compensation methods for digital cameras. One is the image distortion model used in the photogrammetry, and the other is the object distortion model used in the computer vision. Aiming at the problem that the two kinds of distortion models are difficult to achieve generality, we propose a method for transformation of image distortion and objects distortion. First, the transfer relationship between the original image point and the theoretical image point, generated from the known distortion model coefficients and the intrinsic parameters, is used as the virtual measurements. Then, the intrinsic parameters and distortion model coefficients are computed according to the virtual measurements by the least square method. Finally, the three-dimensional (3D) control field calibration result is used to evaluate the precision of the conversion results. The experimental results show that when the camera calibration root mean square error is less than 0.3 pixel, the mutual conversion error of the two types of distortion models is less than 0.5 pixel, which can meet the conversion precision of the sub-pixel.

Compared with the plane target surface, it is more complex for designing light emitting diode (LED) array to produce a uniform illumination distribution on the curved surface. In this paper, the uniform illumination distribution in curved target surface is produced by optimizing the LED array arrangement. In the optimization, firstly, the objective function is constructed to reflect the uniformity of illumination distribution. The objective function takes the coordinates of each LED in the array as variables. Then, the location coordinates of each LED in the array is optimized by simulated annealing algorithm, so that the objective function is minimization. In order to verify the feasibility of the algorithm, we design the cylindrical curved surface, parabolic and sinusoidal curved surface as target surfaces. With the three different kinds of target surfaces, three different LED array arrangements are designed. The three arrays produce uniform illumination distribution on the corresponding target surfaces with the uniformity of 99.0%, 99.3% and 97.0%, respectively. The influence of assembly tolerance of LED arrays on the illumination uniformity of the target surface is also analyzed. The simulation results show that the decrease of the uniformity is no more than 0.3% when the assembly tolerance is within 0.2 mm. This indicates that the design method has good practical value.

A three-stage variable step-size incremental conductance algorithm is proposed, which divides the operating steps into three modes by setting the upper and lower thresholds of the step-adjustment coefficients to ensure that the whole system can still operate with a relatively large step size when the illumination intensity changes drastically. The problem of a slow dynamic response speed for the traditional conductance incremental method is avoided. The simulation results show that, this algorithm can shorten the dynamic response time of this system to 5-6 ms. Moreover, the power oscillation near to the maximum power point is obviously weakened, the power loss of this system is also reduced, and the tracking accuracy is enhanced.

By using the tight-binding model and the eigen-equation method, both the dipole and quadrupole modes of the plasmon in one-dimensional system are studied. The modulation effects of the external field, the size of system and the number of electrons on these two modes are investigated. The results show that, the modes of the plasmon can be controlled by the external field, a symmetrical electric potential field only excites the quadrupole mode, and an anti-symmetrical electric potential field only excites the dipole mode. Based on the size effect of plasmon, the increase of the length of one-dimensional system can reduce the plasmon frequency and enhance the excitation intensity. Based on the charge accumulation effect of plasmon, the increase of the number of electrons before half filling can increase the frequency and excitation intensity of plasmon. Moreover, the excitation intensity of plasmon is symmetric with respect to the half-filling electron number since the excitations of electrons and holes are equivalent. As for the size effect of plasmon, the results calculated by the eigen-equation method can be well fitted by those obtained by the random phase approximation method.

The fluorescence resonance energy transfer (FRET) system of gold nanoparticles and CdSe quantum dots is established via the electrostatic interaction between CdSe quantum dots modified with carboxyl and gold nanoparticles encapsulated with amino. The fluorescence variance in this system with the distance between CdSe quantum dot and gold nanoparticle is investigated. The results show that, the interaction fluorescence intensity and FRET efficiency both decrease with the increase of the distance, which is consistent with that predicted by the Frster resonance energy transfer theory.

The situation that a two-level atom is trapped in each cavity, the two cavities are connected via a fiber, and each atom resonantly interacts with cavity is considered. Geometrical quantum discord (GQD) is used to quantify the degree of correlation between two subsystems, and the GQDs between two atoms and between two cavities in T-shaped coupling cavity system are analyzed. The influences of the atom-cavity and fiber-cavity coupling intensities on GQD are discussed by using the numerical calculation method. The research results show that, with the increase of the atom-cavity coupling coefficient, the GQD between atoms is weakened, but the GQD between cavities is strengthened. With the increase of fiber-cavity coupling coefficient, the GQD between atoms is strengthened, but the GQD between cavities is weakened.

For the same quantum squeezed field, the squeezing degree is different for the measurement schemes of amplitude-quadrature noise and intensity-difference noise, which is theoretically explained. When the output signal has no loss, the squeezing degrees of intensity-difference noise and amplitude-quadrature noise increase with the increase of gain, but the degree of the former is smaller than that of the latter. When the loss is considered, the squeezing degree of intensity-difference noise is larger than that of amplitude-quadrature noise, which indicates that the squeezing degree of amplitude-quadrature noise is more sensitive to loss.

Comparing the soil organic matter (SOM) prediction model based on the broad and narrow bands and the difference in spatial pattern distribution, we validate the feasibility of using satellite remote sensing data to monitor soil basic ecological parameters by ground hyperspectral measurement and analysis of soil. Taking the soil of Tianshan as the research object, we calculate comprehensive spectral index of the broad and narrow band, respectively, using correlation analysis and principal component analysis in the organic matter of unmanned interference area, human interference area, and choosing the comprehensive spectral index with better correlation coefficient and characteristic vector value as the independent variables, using multivariate linear regression model (MLR) and partial least squares regression model (PLSR) to establish respectively the hyperspectral prediction model of SOM in broad and narrow band of unmanned interference area and human interference area. The validation, the comparison and selection the model are carried out. Finally, we analyze and inverse the spatial pattern of SOM content based on the best model of research area. Results show that, through the correlation analysis and principal component analysis of the organic matter and salinity index, vegetation index to establish the MLR and PLSR of organic matter component, we pick out the salinity index 2 (SI2), salinity index 3 (SI3) and ratio vegetation index (RVI), normalized difference vegetation index (NDVI) of narrow band, and the SI1, SI2, RVI, NDVI of broad band in unmanned interference area; we pick out SI1, SI3, RVI and NDVI of narrow band, and SI1, SI2, RVI and renormalized difference vegetation index (RDVI) of broad band. Taking these parameters as independent variables, we build MLR and PLSR models of soil organic matter. By comparing the precision of the models, we find that the PLSR model with narrow band has high precision in human or unmanned interference areas, and determinable coefficient and relative percent deviation are 0.753, 2.01 and 0.819 and 2.14, respectively. Spatial inversion and analysis of SOM in research area are carried out based on the best model above. The mass fraction of organic matter in unmanned interference area is concentrated in less than 10×10-3, and presents the trend of low in middle and high in around. The mass fraction of organic matter in human interference is 10×10-3-15×10-3, presents the trend of low in southwest and northeast, and high around middle north region.

Without influencing the normal operation of engines and space activities, the on-orbit observation of the working state and plume characteristics of the engines is carried out based on the monitoring of ultraviolet radiation and the spectral characteristics of plumes. From the returned test data, one can see that the on-orbit plume ultraviolet radiation test has obtained relatively nice observation results and provides a certain reference for the future research of plume effects and the routine monitoring of plumes.

In recent years, organic photomultiplication photodetectors with external quantum efficiency far exceeding 100% have drawn extensive research attention. This paper firstly presents the typical structures of organic photomultiplication photodetectors and their working mechanisms. Organic photomultiplication photodetectors can be divided into two types depending on the material properties of active layers. One is the small organic molecule photomultiplication photodetector and the other is the polymer photomultiplication photodetector. This paper reviews the progress of these two different types of organic photomultiplication photodetectors. Then, we introduce some important developments in optimizing quantum efficiency, dark current, response speed and spectral performance of organic photomultiplication photodetectors in detail. Later, we briefly show some different explanations proposed by researchers for explaining the working mechanism of organic photomultiplication photodetectors. Finally, we summarize the paper and provide the prospect of organic photomultiplication photodetectors.

Endoscopic optical coherence tomography (OCT) is an important branch of OCT. Endoscopic OCT has become a hot research topic in both endoscopic medicine and OCT fields because of its high-resolution cross sectional imaging capability reaching micron level in a non-contact way. First, the principle, configuration, classification, design, size, resolution, imaging speed, merits and demerits and applied occasions of endoscopic OCT are reviewed. Second, the concepts of specificity and sensitivity in medical field are briefly introduced. Third, the clinical applications and experimental judgement of endoscopic OCT are discussed for the clinical diagnosis in the cardiovascular system, esophagus, stomach and small intestine, and pancreatic tract. Finally, the future development of endoscopic OCT is briefly discussed.

As important experimental devices, solar simulators are widely used in the fields of space technology, aerospace and solar energy industry. During the development of solar simulator, the joining of light emitting diode (LED) has an important impact on the property enhancement of solar simulator. Firstly, the development background of solar simulator is briefly introduced, and the advantages and value of light source LED are expounded. Then, the standards of performance evaluation for solar simulator are enumerated and every standard is introduced and compared with each other. Structure, control and optical design of representative LED solar simulator at home and abroad are narrated. Comparisons of spectral matching degree, irradiation inhomogeneity and irradiation instability are made. Finally, priority research and development tendency of LED solar simulator are summarized.

Taking the commercial salt as a model sample of granular matters with complex size and component distribution, we study the stability of laser-induced breakdown spectroscopy (LIBS) from microelements in complex granular matters. We measure the intensities of emission spectral lines, relative standard deviation and signal to noise ratio from four typical microelements (Ca with mass fraction of 800×10-6, Sr with mass fraction of 35.1×10-6, Mg with mass fraction of 6.4×10-6, and Fe with mass fraction of 1.7×10-6) in the salt sample in the band from 250 nn to 465 nm to determine the most optimal experimental conditions for synchronously detecting the four microelements. Based on these optimal conditions, we quantitatively obtained that the LIBS stability of the four microelements is above 10%, 14%, 13% and 28%, respectively. This indicates that LIBS technology has the ability to detect microelement with mass fraction of 10-6 in salt, providing experimental references for the detection of microelements in complex granular matters using LIBS in on-line industrial processes.