Taking the Bessel and Bessel-Gauss vortex beams shaped by a circular aperture as examples, beam spreading and phase singularities' behavior of approximate non-diffracting vortex beams in turbulent atmosphere are numerically simulated. The simulation results show that, the spreading of Bessel-Gauss vortex beam caused by the atmospheric turbulence is less than that of the Bessel vortex beam, and the algebraic sum of the phase singularities of Bessel-Gauss vortex beams remains close to the topological charges of the input vortex beams. In addition, the algebraic sum fluctuation deviation of the phase singularities of Bessel-Gauss vortex beams is smaller than that of Bessel vortex beams in long distance propagation. As the information carrier, Bessel-Gauss vortex beams have potential application in free space optical communication.

We propose an image color correction algorithm based on a double transmission underwater imaging model to solve the color distortion problem associated with the underwater images. First, we divide the transmission as direct component transmission and backscatter component transmission based on the underwater imaging model. Subsequently, the backscatter component transmission is obtained by a red-dark channel prior, the background light is accurately estimated, and the direct component transmission of three channels is obtained based on the non-degenerate pixel points. Finally, both the transmissions are inserted into the imaging model to obtain the restored image. The experimental results demonstrate that the proposed algorithm can effectively remove the color cast of underwater images by relying only on the physical model.

Spin-orbit-coupled ultracold atom system becomes an important platform to simulate Zitterbewegung. Current experimental study of Zitterbewegung is in a two-component atomic system, while the existed three-component theoretical study on spin-orbit coupling is difficult to realize in experiments. In this paper, based on the experimentally realizable three-component spin-orbit-coupled system, we analyze the Zitterbewegung and reveal that the Zitterbewegung has many oscillation frequencies. In the presence of harmonic trap potentials, Zitterbewegung oscillation possesses more rich physical characters.

A radiation calibration method is proposed for the compensation of output gray values of an infrared spectrometer system based on the variation in ambient temperature. First, the reasons for the output gray-value shift of the infrared spectrometer system in the process of radiation calibration and measurement are analyzed; subsequently, the functional relationship between the change of drift and ambient temperature radiation is obtained. Then, the laboratory radiation calibration equation and radiation calibration equation at different ambient temperatures after compensation are determined by experimental radiation calibration using the uncooled long-wave infrared grating spectrometer developed in our laboratory. Finally, the accuracy of the radiation measurement using the compensated radiation calibration equation at different ambient temperatures is experimentally verified. The results show that the output gray-value error of the spectrometer system can be significantly reduced by drift compensation at different ambient temperatures, and the error is less than 2.4%. The measurement accuracy of the uncooled long-wave infrared spectrometer for infrared radiation is greatly improved in this research.

Two-dimensional (2D) gratings are the key elements of optical encoders in lithography machines. Herein, an ultra-precision laser direct writing system is proposed. Based on the ultra-precision platform, we obtain a 2D grating mask with grid line density of 1200 line/mm after double exposure by rotating the substrate by 90°. The atomic force microscopy and scanning electron microscopy images indicate that the profile of the 2D grating mask is clear and its spatial uniformity is excellent. These results demonstrate that the proposed ultra-precision laser direct writing system effectively fabricates a 2D grating mask, showing promise in the fabrication of large, high-precision 2D metrological gratings.

The modulation principles of the two different single-sideband signals based on independent dual-driving Mach-Zehnder modulator (DDMZM) and the in-phase/quadrature modulator are introduced theoretically. Based on the study of 100 Gbit/s 16-quadrature amplitude modulated single-sideband signal after 75-km standard single-mode fiber transmission, we analyze the principles of parameter optimization of the two approaches. The Kramers-Kronig (KK) algorithm is used to recover the single-sideband signal and eliminate the signal-to-signal beating interference (SSBI) at the receiving end. The results show that, due to effects of the modulator nonlinearity and the carrier signal power ratio, the KK receiver based virtual carrier approach can reduce the received optical power by about 2.3 dB compared with the DDMZM approach at the 7% hard-decision forward error correction threshold with bit error rate of 3.8×10-3.

We propose a lightweight secure identity authentication encryption (CH-CNA) mechanism based on the cryptographically generated address (CGA) algorithm and the hash generated address (HGA) algorithm to satisfy the strict security requirements of all the parties in the internet multi-servicing context while reducing the cost that is typically associated with the introduction of security mechanisms. In particular, the proposed mechanism analyzes the communication security challenges faced by the software-defined optical access networks (SDOAN). The CH-CNA mechanism follows the information interaction method of the OpenFlow protocol, and the first and non-first authentication bindings are achieved among the communication nodes using the CGA and HGA algorithms without any third-party participation. During the authentication binding process, the attacker is prevented from forging or tampering with the authentication interaction messages, establishing an end-to-end trusted connection in the access network. The proposed CH-CNA mechanism is tested using the OMNeT++ network simulation software. The experimental results demonstrate that the proposed mechanism can reduce the average computational overhead and blocking rate because of malicious attacks and ensure secure interaction among the communication nodes, which conforms to the definition of lightweight.

A joint transfer scheme of frequency and one pulse-per-second time signals based on the same wavelength is proposed to meet the time delay measurement requirements of large-range and high-precision fiber-optic links. The scheme combines the coarse results of the one pulse-per-second time counting method and fine results of frequency signal phase-comparison method to achieve high-precision and large dynamic measurement of the true delay of the fiber link. We construct an experimental system to verify the consistency of the coarse and fine measurements and measure the absolute delay of the signal over 25 km of optic fibers under severe temperature change conditions. The experimental results demonstrate that the proposed method can effectively combine the large-range advantage of the one pulse-per-second counting method with the high-resolution advantage of the phase measurement method.

A coherent orthogonal frequency-division multiplexing passive optical network (OFDM-PON) system based on optical frequency comb (OFC) and injection locking local laser is proposed. Optimum OFDM signal power, optical local oscillator (LO) power and injection ratio are found by both theoretical calculation and experiments. The bit error rates (BER) performance of three kinds of downlink transmission are experimentally compared in which LO is provided by semiconductor optical amplifier (SOA), wide-linewidth slave laser and narrow-linewidth slave laser after 25 km single mode fiber (SMF) transmission. The results show that injection locking can improve the receiving sensitivity without affection by the inherent linewidth of the slave laser, and provide coherent light for uplink transmission. Therefore, the proposed system can reduce cost and provide the possibility for the application of the optical coherent detection technology in access networks and data-center interconnections.

Phase-stabilized microwave signal transmission has been widely used for radar, space observations, and satellite navigation. To address the problems of low transmission efficiency and slow speed of active compensation in a point-to-point phase-stabilized transmission scheme, herein, we propose a scheme for point-to-multipoint microwave signal transmission via optical fiber links using passive phase correction, which is required for achieving a large compensation range and multiple access points. At the local end, we use a power splitter to divide the microwave signal into two paths, which are used as the signal to be transmitted and detection signals after frequency division. The signal to be transmitted is mixed with the detection signal following a roundtrip transmission via the optical fiber to obtain a down-converted signal. The down-converted signal is then transmitted to the remote end through the same fiber link to be mixed with the forward detection signal for one-trip transmission. This generates a stabilized microwave signal, and the stable point-to-multipoint phase transmission is realized from a rational design of the structure. Experimental results show that the root mean square (RMS) timing jitter of a 2-GHz signal in this multi-link distributed structure is 0.968 ps across a 10-km fiber link, whereas the RMS timing jitter of a single-link distributed structure is 1.606 ps over an 11-km fiber link.

In order to study the transmission characteristics of vortex beams in a photonic crystal fiber (PCF), we propose three different vortex PCFs, i.e., triangular lattice ring photonic crystal fiber (TLPCF), inverse-parabolic graded-index profile photonic crystal fiber (IPGIF), and sixfold photonic quasi-crystal fiber (SPQCF). By using the vector finite element method, we analyze the transmission characteristics of vortex modes in three PCFs. The results indicate that the effective refractive index difference between adjacent vector modes is larger than 10-4, which is conducive to the transmission of vortex beams. The dispersion coefficient of TLPCF is the smallest, and that of SPQCF is the largest. Both of TLPCF and SPQCF can maintain the flat dispersion over a wide wavelength range (1400-1700 nm). The confinement losses of these three fibers are below 1×10-7 dB·m-1, so that light can be confined in fiber core well. The nonlinear coefficients of the three different PCFs are in the order of 10-3, and the stable transmission distances of the three different PCFs are longer than 1 km.

A low-complexity spectrum resource allocation algorithm with near-optimal system throughput is proposed to resolve the conflict between high system throughput and low complexity of the multi-cell resource allocation algorithm for indoor ultra-dense visible light communication (UD-VLC) networks. Firstly, through establishing the optimal model of the resource allocation problem in each cell, we derive the conclusion that the problem is a convex optimization problem. Then, the analytic formula of the normalized scaling factor of each terminal for resource allocation is derived after reasonable approximate treatment, and the resource allocation algorithm is proposed. Finally, the complexity analysis shows that the proposed algorithm has polynomial complexity, which is lower than the classical optimal inter-point method. The simulation results show that the proposed method achieves 57% performance improvement on average system throughput and 67% performance improvement on quality of service (QoS) satisfaction against the required data rate proportion allocation (RDR-PA) method.

The abrasion of a crosshead bushing is one of the important reasons for the failure of the compressor under normal circumstances. To ensure the safe and efficient operation of the compressor, it is necessary to monitor the temperature of the bushing in real time to determine the abrasion. For complex working conditions in petrochemical industry, a wirelessly coupled fiber-Bragg-grating (FBG) sensor is proposed and designed to wirelessly transmit optical signals, thereby realizing the extraction of bushing’s temperature signals. However, in order to solve the problem of excessive demodulation temperature difference caused by the U-type signal at the center wavelength generated during a dynamic operation, the insertion-loss threshold is used to reduce the temperature change from 4 ℃ to less than 0.1 ℃. This improves the accuracy of temperature demodulation and realizes the wireless monitoring of temperature.

Aiming at the problems of optical alignment in optical transform watermarking algorithm and the security of optical cryptosystem, an optical watermarking method based on hyper-chaotic mapping and Gyrator transform is proposed. The hyper-chaotic phase mask is constructed by using the Chen 4D hyper-chaotic system, and then the vortex light constructed by the Fresnel zone plate and the radial Hilbert mask is used to illuminate the hyper-chaotic phase plate. Finally, the encrypted watermarking image is embedded into the host gray image by means of Gyrator transform to realize optical information hiding in the Gyrator domain. The Gyrator inverse transform is used to extract the watermark information embedded in the target image. The experimental results show that the algorithm can extract high-quality watermarking information from highly imperceptible target images. The encrypted target image has a high signal-to-noise ratio and strong correlation with the host image. It can effectively resist salt and pepper noise and Gauss noise attacks with intensity coefficients of 0.06 and 0.8 respectively, and has good robustness against attacks with less than 50% occlusion rate and 80 compression factor. The encrypted target image has a similar statistical distribution compared with the original host image, which realizes information hiding well.

In traditional multi-exposure image fusion methods, once the target moves, the phenomenon of “ghosting” occurs in the final fused image. Most existing de-ghosting algorithms inherit substantial data from the reference image. Once the underexposure/overexposure occurs in the reference image, the final fusion result is affected. To remedy this, herein, a multi-exposure image fusion de-ghosting algorithm based on image block decomposition is proposed. First, the reference image is divided into two areas, i.e., normal exposure and underexposed/overexposed areas, both of which are individually processed. To detect the ghost area more accurately, the proposed algorithm decomposes the multi-exposure image block into three independent parts, i.e., signal structure, signal intensity, and average intensity. Ghost detection is then performed by detecting structurally consistent image parts, following which inconsistent parts are removed, the three image parts are fused, and the required image parts are reconstructed and added to the final fused image. Experimental results of this algorithm's validation show that compared to existing de-ghosting algorithms, the proposed algorithm achieves better visual effects and improves computational efficiency.

The compensable range of the existing electronic image motion compensation method is limited in scanning direction. To solve this problem, a digital time delay and integration (TDI) method suitable for wide-range image motion variation in scanning direction is proposed. First, based on the image motion calculation results, whether the image motion is within the range of electron frequency compensability is judged. Then, the image motion mismatch in scanning direction will be adjusted by image interpolation and matched pixel accumulation when it is not within the compensable range. A digital TDI algorithm model suitable for arbitrary image motion is constructed. Finally, the proposed algorithm is verified by experiments. The experimental results show that when the total image motion of 96-stage integration is much smaller than one pixel size, the image quality of the proposed algorithm is similar to that of the traditional TDI method, but when the total image motion of 96-stage integration is larger than one pixel size, which exceeds the compensable range of the electronic method, the image quality of the proposed algorithm is much better than that of the traditional TDI method. The traditional TDI method causes serious aliasing and the image quality drops sharply; however, the proposed algorithm can maintain the image quality effectively. Both the image motion transfer function and the similarity correlation measure can be improved by 0.11 using the proposed algorithm.

Aiming at systematic error sources in a Mueller matrix imaging polarimeter, we propose a simplified analytical method based on the approximate matching of the ideal coefficients of Fourier series of the intensity curve with the real ones. By using the method, a linear relationship between the deviation of the Mueller matrix and the parameter of the error source is built. The analytical expression for random error caused by the azimuthal angle is complex, so an equivalent noise model is proposed to characterize the impact of misalignment from the view of statistics. Based on the simplified models above, we conduct a comprehensive analysis for the measured Mueller matrices influenced by six kinds of systematic error sources and two kinds of random error sources. The simulation for the measurement of a typical Mueller pupil of the lithographic projector is performed. The results verify the accuracy of the proposed method.

In a gene sequencing system, the ensquared energy is an important parameter for realizing accurate recognition for the base. Nevertheless, the displacement between wafer and camera, which is caused by vibration and position error of wafer stage while photographing, will decrease the image quality and further influence the ensquared energy. This study establishes the relationship model between the dynamic factors and ensquared energy. Static and dynamic experiments are carried out on the sequencing platform. The results reveal that the ensquared energy has linear relationship with the location standard deviation of the wafer stage. If the ensquared energy value is required larger than 65%, the location standard deviation should be controlled below 140 nm. Meanwhile, the ensquared energy calculated by using the DNA nanoball image collected in the dynamic experiment is in accordance with the experimental conclusion. The dynamic performance parameters of the wafer stage in the gene sequencing system can be allocated reasonably.

We develop an intelligent method to monitor the long-term instrumental response degradation of the Fengyun-3A (FY-3A) satellite medium-resolution spectral imager (MERSI). This method assesses the instrumental response degradation during the interval between the capturing of two images using an iteratively reweighted multivariate alteration detection (IR-MAD) algorithm to statistically select invariant pixels from the different-temporal satellite images, which are obtained from the same geographic region. First, the IR-MAD algorithm is used to analyze the invariant pixels from the image scene; subsequently, the orthogonal regression of invariant pixels from two images is conducted to obtain the relative degradation of the sensor during this interval. Next, all the long-term sequence images are processed in a similar manner and the polynomial fitting is used to obtain the relative degradation curve of the sensor over the entire period of time. Herein, we conduct this procedure using the data of FY-3A/MERSI obtained from north Africa and northwestern China, and compare the obtained results with the instrumental degradation results obtained from other relevant researches. The verification results denote that the proposed method is in good agreement with other methods (the difference is less than 2%). The results obtained in north Africa are consistent with those obtained in northwestern China (the differences are less than 1% in majority of the bands), indicating the universality and reproducibility of the proposed method.

In order to improve the centroid location accuracy of fine guidance sensor in dynamic environment, a two-step restoration method is proposed to solve the problem of star spot trailing caused by angular motion of carrier and small amplitude random vibration. Constrained least squares filtering is used to eliminate the long tail of the star spot caused by the angular motion of the carrier according to the fuzzy kernel function detected by the two fast Fourier transforms of the blurred star spot. Aiming at the residual blurring caused by small amplitude random vibration of the carrier, the clear star spot gradient distribution prior is used as a regular constraint to iteratively blind restoration of the coarse restoration results. The half-quadratic optimization algorithm is introduced to solve the non-convex cost function to improve the convergence speed of the iteration. The experimental results show that the restored star spot is close to the Gauss distribution in the dynamic environment of 4000 μrad/s angular velocity, and compared with the inverse filtering and R-L methods, the peak signal-to-noise ratio is 61.9% and 32.9% higher and the error of centroid location is 59.9% and 43.4% lower, respectively.

This paper proposes a new laser interferometer which is suitable for measuring the profile of an optical lens with a long focal length. Full-field heterodyne phase-shift technology is used to suppress the effects of factors such as vibration and the atmosphere on long-cavity interferometry. The heterodyne coherent measurement of the measured and reference wavefronts is achieved using a Twyman-Green interferometer structure. Experimental equipment is developed, and an experiment is conducted to prove that the novel setup can suppress the influences of external vibration and atmospheric turbulence on the measurement accuracy,achieving a long-cavity measurement with a root mean square repeated measurement accuracy of 0.45‰λ. Thus, this technology can prove to be a valuable alternative to traditional long-cavity interferometry.

Aiming at the large measurement error and low accuracy problems caused by refraction when conducting underwater measurement based on non-parallel stereovision system, a measurement model of underwater stereovision system is built via refraction light path. Given the relative position relationship between two cameras, a parameter calibration method which is suitable for the measurement model is improved based on Agrawal's algorithm. To verify the feasibility and robustness of the improved method, the underwater calibration experiments are carried out. Experimental results show that, for the parameter of normal vector of waterproof cover, the results of the improved method are closer to the actual results than that of Agrawal's algorithm. The measurement model of underwater stereovision system calibrated in this paper is applied to measure the standard length between the calibration points on the underwater target. The average measurement error is -0.0134 mm, and the maximum error is 0.2073 mm, which is equivalent to the measurement accuracy of stereovision system in air.

To achieve high polarization measurement accuracy of a particulate observing scanning polarimeter (POSP), onboard polarization calibrators are designed and a novel measurement method for their polarization state value is studied. First, the instrument overview, measurement principle, and polarization calibration model of the POSP are introduced. Second, based on the instrument characteristics, we proposed earthshine combined linear polarization calibrator (LPC) or non-polarization calibrator (NPC), two types of standard polarization state sources, and then design the LPC and NPC in detail. Finally, Marius's law is used to determine the polarization state value of the LPC. Data from observations of the satellite nadir are utilized to choose a underlying surface with a degree of linear polarization less than 0.4 as the effective light source for NPC. The two calibrators meet the requirements of full path, full aperture, and end-to-end calibration, ensuring the long-term polarization measurement accuracy of 0.005.

The Mie scattering interference induced by aerosol on gas temperature retrieval and the errors of line width of the Fabry-Perot interferometer (FPI) instrument function, scattering angle, gaseous bulk viscosity, and pressure are studied based on the spontaneous Rayleigh-Brillouin scattering spectra of nitrogen simulated at the temperature of 298 K and pressure range of 20265.0-810600.0 Pa. The simulation results show that when the error of the instrument function line width is less than or equal to 5 MHz, the error of the scattering angle is less than or equal to 0.2°, bulk viscosity error is less than or equal to 0.2×10-5 kg·m-1·s-1, and relative error in pressure is less than or equal to 3%, a maximum absolute temperature error of 1.7 K caused by the single parameter error may occur. When the relative intensity of the Mie scattering is 0.3-2.5, the temperature retrieval errors are usually lower than 2 K. In addition, the spontaneous Rayleigh-Brillouin scattering experiment with a 90° scattering angle in nitrogen is performed at the temperature of 298 K and pressure range of 70927.5-709275.0 Pa. The temperature is retrieved according to the measured spectra after parameter optimization. The results show that the experimental results are in good agreement with those of the simulation. For simulation-based parameters with the same errors, the absolute temperature errors obtained by the experiment are lower than 1.2 K. This study is helpful in achieving the high-precision absolute measurements of gas temperature and accurate analysis of the gas state under different pressures.

We design and fabricate a 1.55-μm high-speed high-power distributed feedback laser array based on the AlGaInAs material. We adopt the AlGaInAs material that exhibits good temperature characteristics and high differential gain as a quantum well and waveguide layer to achieve high power and wide bandwidth. Further, we use a dilute waveguide to reduce internal loss and optimize the far-field divergence angle; subsequently, a suspended grating is used to optimize coupling coefficient, and the single-mode stable operation with large injection current is realized. Based on this optimized material structure, we fabricate a 1.5-μm laser array at five different wavelengths. In continuous-wave operation at room temperature, each laser in the array can achieve a single-mode lasing power of greater than 100 mW (the maximum output power of a single laser is 160 mW), a side-mode suppression ratio of greater than 55 dB, a small-signal-modulation bandwidth of 7 GHz, the narrowest linewidth of 520 kHz, and a relative intensity noise of -145 dB/Hz.

The laser source is an important part of a cold atomic clock for laser cooling and atomic population detection. This study selects a 1560-nm fiber laser and a fiber amplifier as the seed laser and the amplifier laser, respectively, in a rubidium cold atomic clock system because of the technical maturity of the industrial products. The cooling laser is obtained at 780 nm by doubling the frequency of the amplified laser using a nonlinear frequency doubling crystal. Further, the laser frequency is locked to the rubidium transition line via the saturation absorption frequency stabilization technique. A part of the cooling laser passes through an electro-optic modulator and an acousto-optic modulator with a frequency shift of 6.8 GHz to obtain the repumping laser. The lasers are provided to the cold atomic clock after ensuring appropriate power distribution. The amplifying, frequency doubling, and noise characteristics of the key components in the laser device are verified. Subsequently, the beating signal between the cooling laser after frequency doubling and the optical frequency comb locked to an ultra-stable laser denotes that the line width of the cooling laser is approximately 74 kHz and that the short-term stability is half an order of magnitude higher than that of the external cavity semiconductor laser which is used in our laboratory. Furthermore, the application of such a laser light source to the cold atomic clock can reduce the limitation of fountain clock stability which can be attributed to the detection of the laser frequency noise.

To address the poor robustness of single feature in a complex scene and tracking failure caused by background interference and object occlusion, this study proposes a correlation filter tracking algorithm that combines adaptive feature fusion and adaptive model update. Based on kernel correlation filtering, the proposed algorithm performs weighted summation on the response maps of different features by adopting the average peak-correlation energy method to realize adaptive feature fusion of response maps. The adaptive weight is calculated as the confidence according to the peak characteristics of the response maps to determine the update rate of the model,thereby realizing the design of an adaptive model updating method. Experimental results demonstrate that the algorithm can adapt to complex scene changes, such as background disturbance, object occlusion, and rotational motion. Compared to popular correlation filtering tracking algorithms, the proposed algorithm increases the average distance and overlapping precision by 2.64% and 1.54%, respectively.

Existing restoration methods perform virtual restoration of computer-aided cultural relics with low accuracy and speed. To address this issue, a new reassembly method of cultural relics based on feature Point matching of fracture surface is proposed. First, the improved internal shape signature method is used to extract potential feature points of fragment fracture surfaces. Then, the covariance matrix of geometric features of adjacent feature points is calculated to construct feature descriptors. The logarithmic Euclidean Riemann method is then used as the similarity measure criterion, and the initial point pair set is obtained based on the bidirectional nearest neighbor method. The optimal matching set is obtained by eliminating mismatching pairs based on the canonical correlation analysis method. Finally, the least square method is used to calculate the rigid body transformation matrix to align the fragments and the iterative closest point algorithm is used to achieve precise alignment, thereby realizing fragment reassembly. Experimental results show that the proposed algorithm has fewer feature points compared with traditional algorithms; the descriptor is simple and robust, which effectively improves the efficiency and accuracy of fragment reassembly.

Tracking algorithms with Siamese network use the offline training network to extract features from the target for matching and tracking. In the offline training process, the network learns the common features of similar goals. In the case of interference from similar targets, using common features to express specific targets will lead to degradation of tracking performance and even loss of targets. To improve the feature discriminative ability for similar targets, we update the parameters of network online, and make the network further learn the specific characteristics of the current target based on the common features. The proposed method can not only effectively distinguish the target and background, but also eliminate interference from similar targets. We conduct a large number of experiments on the OTB50 and OTB100 databases. The results show that the proposed algorithm can improve the discriminative ability to features extracted by the network and achieve robust tracking of the target.

Monocular pose estimation is a basic and important problem in computer vision, being widely used in robot positioning, virtual reality and image precision measurement. In practical application, the coordinates of reference points inevitably contain outliers which may lead to an estimating result far from the true value. Therefore, an adaptive weighted robust orthogonal iteration algorithm is proposed. To improve robustness, this algorithm uses a robust estimation method to find out the outliers and suppress their impaction by allocating them smaller weights. The experiment results show that the proposed algorithm is robust with high accuracy. This algorithm can effectively restrain the influence of outliers with different number and levels. When there are 8 outliers of 60 pixel in 20 reference points, the accuracy of this method is 2 and 1 orders of magnitude higher than that of classical orthogonal iteration algorithm and weighted orthogonal iteration algorithm, respectively.

Salient object detection has attracted considerable attention in the field of the machine vision, with a wide range of applications. This study proposes a salient object detection algorithm based on the dual-attention recurrent convolution to overcome the limitations associated with the existing algorithms, i.e., uneven salient region detection and fuzzy edge representations. A dual-attention module consisting of pixel- and channel-wise attentions is added to a backbone U-Net fully convolutional network to preprocess the shallow convolutional features before skip-layer connection, and reduce noise and clutter interference. This improves its salient region detection performance. Then, following the backbone network, a recurrent convolutional module enhances the edge representation of the prediction region by combining the final prediction map with the shallow convolutional features. The results of experiments on three open datasets show that the proposed algorithm is better able to highlight salient regions and refine their edges than other correlation algorithms.

Video-based person re-identification problems are caused by perspective changes, lighting variations, background clutter, occlusion, appearance similarity, motion similarity, and mismatch resulting from the distance difference of same person with different modal features. This study proposes a video-based person re-identification method that combines multi-level deep feature representation and ordered weighted distance fusion. During the stage of person feature representation, the multi-level deep feature representation network proposed herein not only learns the space-time features of the persons in video sequences but also acquires the persons' global and local appearance features. In the stage of the ordered weighted distance fusion, the feature representations of persons are firstly input into distance metric learning, and the independent distances of persons under three types of features are calculated. The fusion algorithm then sorts the distances to optimize distance weights according to distance ranking. Finally, to accurately match a person, the algorithm fuses the three types of distances to obtain the final distance. Experimental results compared with the results of related methods in public datasets show that the proposed method not only improves the recognition rate of video-based person re-identification but also possesses abundant and integral ability for person feature representation.

Two type-II superlattices [InAs (10 monolayer, 10 ML)/GaSb (10 ML)] with 10 and 20 periods are grown on GaAs substrates via molecular beam epitaxy and growth interruption method based on the control of the shutter switch sequence. In the experiment, the regulation and analysis of the growth parameters are based on software simulation. The simulation denotes that As-Sb substitution is efficient and the stress of the interface is effectively reduced. Further, the surface morphologies of the superlattice samples are tested and characterized by the double-crystal X-ray diffraction and atomic force microscopy. The stresses of the superlattice samples of InAs and GaSb are reduced to 0.64% and 0.56%, respectively, and the root mean square roughnesses are 0.81 nm and 0.45 nm, respectively. The results indicate that this technique is useful for the fabrication of devices.

The effects of LED monochromatic light quality of different colors on the growth of phaeodactylum tricornutum cells, their fucoxanthin content, and the expression levels of genes related to fucoxanthin biosynthesis are investigated. The results show that red light, green light, and purple light promote the growth of phaeodactylum tricornutum cells. In addition, the number of algal cells significantly increases by 12.44% on the 6th day under red light treatment (P<0.01) compared with that in the control group. Yellow light and blue light inhibit the growth of phaeodactylum tricornutum cells, and the aging rate of algal cells under green light and purple light treatments is higher than that in the control group. Compared with the control group, the fucoxanthin content of phaeodactylum tricornutum treated with red light and purple light increases by 16.61% and 26.78%, respectively, and that of phaeodactylum tricornutum treated with blue light and green light significantly reduces (P<0.01). The changes in chlorophyll and fucoxanthin content, which are related to photosynthesis, are basically the same under all treatments. Evaluation of the expression levels of genes related to fucoxanthin biosynthesis shows that among zeaxanthin cyclooxygenase gene (zep), phytoene synthase gene (psy), ξ-carotene dehydrogenase gene (zds), lycopene β-cyclase gene (lcyb), carotene isomerase gene (crtiso), and phytoene dehydrogenase gene (pds), the expression level of the key gene psy, is consistent with the change in the fucoxanthin content, whereas the expression levels of pds and lcyb are significantly upregulated under red light treatment. Therefore, fucoxanthin biosynthesis in phaeodactylum tricornutum under treatments with light quality of different colors is indicated by the expression levels of genes related to fucoxanthin biosynthesis, and it is possibly related to photosynthesis.

Simultaneous phase-shifting interferometric microscopy is proposed herein to measure the phase of red blood cells for leveraging the characteristics of slow blood flow and a small number of red blood cells in microvessels. A characteristic volume model of red blood cells is established to match characteristic red blood cells from multi-frame phase maps. Then, slow blood flow detection is realized. A Ф100-μm microvessel prototype with a flow rate of 0.1-1.0 mm/s is prepared using Alsever’s solution of bovine red blood cell. A simultaneous phase-shifting interferometric microscopy experimental setup based on a micro-polarization array is constructed to validate the feasibility of the proposed detection method, and the measurement error of the blood flow velocity is no greater than ±11.2%.

An imaging optical system with large relative aperture and field of view was designed based on a modified Mangin mirror. The aberrations of the modified Mangin mirror are analyzed and a design method is proposed for it. The optical system adopts a combination of an improved Mangin mirror and a catadioptric optical system. The relative aperture is 1/1.8, field of view is 4°× 4°, working band is 450-850 nm, and focal length is 380 mm. The imaging detector is a CMOS detector with pixel of 2 μm×2 μm. The modulation transfer function value is close to the diffraction limit and greater than 0.5 at a Nyquist frequency of 250 lp/mm. The secondary mirror of the system is designed based on a Mangin mirror and an achromatic lens. Based on the spherical aberration and sine aberration obtained from the preliminary optimization analysis of the initial system structure, the focal power of the achromatic Mangin mirror is solved by the PW method. Based on achromatic conditions and residual chromatic aberration of the system, the focal powers of three surfaces of the achromatic Mangin mirror are solved and the radii of the surfaces can be calculated. The system has small monochromatic and chromatic aberrations and good imaging quality.

Universal time (UT1) is an indispensable parameter in applications of geodesy and navigation. Currently, an UT1 parameter per day can be obtained from the international Earth rotation service (IERS). However, UT1 parameters cannot be measured and obtained in real time on any day. Large-scale fiber optic gyroscopes (FOGs) can measure and provide high-temporal-resolution measurements of variations in the Earth’s rotation angular rate; thus, FOGs may provide a way to monitor UT1 in real time. Herein, we report the design of a novel UT1 calculation method based on the existing large-scale FOG measurement platform and the basic principles of FOG measurement. Data measured from FOG by this new method are analyzed to verify the method’s accuracy and feasibility for implementation. The UT1 parameters are preliminarily calculated by measuring data from the large-scale FOG; the time interval for UT1 parameter acquisition is also shortened to 5 min. Thus, based on the large-scale FOG, the proposed method has the potential to become a new method of UT1 measurement.

A three-layer decomposition model is used to downscale the surface temperature of the study area via four different surface feature factors and their combinations. Experimental results show that the three-layer decomposition model using multi-surface feature factor combination obtains higher downscaling accuracy than that using a single factor, and the root mean square error increases from 0.813 K to 0.763 K; the main source of error is the architectural area. To study the urban heat island effect, this study uses the heat field intensity index and heat field variation index for evaluation; both evaluation indexes indicate that the accuracy of the multi-factor model is better than that of the single factor model.

Synthetic aperture ladar (SAL) is a combination of synthetic aperture and ladar, which has developed rapidly in recent years. Since the wavelength of the SAL is short, high-resolution imaging can be achieved in a short period of time. However, short wavelength also brings other problems. For airborne SAL, the wavelength is less than the vibration amplitude of the airplane by 1-2 order of magnitude, and the vibration of the airplane results in a great phase error to the echo. It is difficult for the inertial navigation system (INS) to achieve the positioning accuracy at the laser wavelength level, so the data-based self-focusing is necessary in SAL imaging. In this paper, a full aperture imaging algorithm based on minimum entropy autofocus (MEA) and deramp is proposed to process the SAL real data. The imaging results verify the effectiveness of the proposed algorithm.

The spatial resolution and modulation transfer function (MTF) are important parameters for image-quality evaluation of high-spatial-resolution satellite optical sensors. They objectively reflect the imaging quality of a remote-sensing imaging system. We present a method using a radial target for spatial-resolution measurement that employs a large-area target with uniform reflectivity. This method depends on the relationship between the target modulation degree, object modulation degree, and image modulation degree in the pupil of the sensor. It can accurately determine the on-orbit MTF value of a spaceborne remote-sensing imaging system without atmospheric effects as well as the MTF value of the atmosphere. Experimental results show that the proposed radial-target method can simultaneously determine the spatial resolution and the on-orbit MTF value of the spaceborne remote-sensing imaging system. The real-time MTF value of the atmosphere is 0.7519. The difference between the on-orbit MTF value measured by our radial-target method and that measured by the knife-edge method is less than 5%. The proposed method can provide on-orbit image-quality evaluation of high-spatial-resolution satellite optical sensors.

We propose a ground segmentation algorithm for various urban environments to overcome the problems of under-segmentation and over-segmentation on sloped roads, obstacles and ground junctions. First, the point cloud is linearly arranged based on the horizontal angular resolution of the lidar. Then, the ratio of the distance from front and rear points to the lidar is used to remove abnormal noise, and the height threshold is adaptively adjusted by using the distance from each point to the lidar and slope value. Finally, ground segmentation is performed using the adjusted global and local height thresholds. Through experimental analysis of three different types of urban roads, it is verified that the proposed algorithm can effectively distinguish the point cloud between the obstacle and ground and slope surfaces in different urban scenarios. The segmentation accuracy can reach 98% on average, and the average time consumed is 2 ms.

In view of the large amount of soil hyperspectral data and obvious spectral information redundancy, this paper aims to compare prediction abilities of multiple feature variable selection methods for estimating soil organic matter. The stability competitive adaptive reweighted sampling (sCARS), successive projections algorithm (SPA), genetic algorithm (GA), iteratively retained information variables (IRIV), and sCARS-SPA are used to select the characteristic variables from full spectral data. Based on these characteristic bands and full spectral bands, partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) models are used to predict the soil organic matter content. The results show that the PLSR and SVM models combined with variable selection can not only improve the efficiency of the model, but also improve the model prediction ability over the full bands. The accuracy of RF model constructed with characteristic variables is not obviously improved, but the variable number in the construction model is significantly reduced and the modeling efficiency is greatly improved. Overall, the RF model’s accuracy is better than those of the SVM model and the PLSR model. The variable number of the prediction model from the combination of IRIV and RF is only 63, and the coefficients of determination (R2) from calibration set and validation set are respectively 0.941 and 0.96, and the relative deviation for the validation set RPD is 4.8, showing a very good prediction capacity. Compared to modeling based on the full bands, the combination of characteristic variable selection and regression methods can effectively improve the modeling efficiency while ensuring the accuracy of the model.

Chlorophyll content in canopy plays an important role in reflecting the growing status of vegetation. To achieve high accuracy of chlorophyll content estimation based on hyperspectral data, the spectral reflectance and chlorophyll content in cotton canopy are measured from field observation. Original spectral data is transformed to calculate the hyperspectral parameters. The correlation between hyperspectral parameters and chlorophyll content is analyzed and a back propagation (BP) neural network model for estimating chlorophyll content in cotton canopy is established. Results show that after continuum-removal transformation, the correlation between canopy reflectance and chlorophyll content improves by 10.7% in the spectral bands of 560-740 nm, which is better than that of the original spectrum and the first-order differential spectrum. Vegetation indices, such as mSR, mND, NDI, and DD, which are established using the original spectrum and continuum-removal spectrum, show a high correlation with chlorophyll content under both spectral conditions with a correlation coefficient of approximately 0.8. In the BP neural network model, the model determination coefficient based on continuum spectral indices is 0.85, and the root-mean-square error and relative error are 1.37 and 1.97%, respectively. This result is better than that of the model based on red-edge parameters, original spectral vegetation indices, and first-order differential spectral indices. This study provides important theoretical basis and technical support for practical application of chlorophyll content estimation in crops.

Near-infrared spectroscopy (NIRS), combined with chemometrics methods, is applied to rapid quantitative determination of oleic acid and linolenic acid in camellia oil blends. 76 camellia oil samples are prepared and used for near-infrared spectral collection. Different spectral preprocessing methods are applied to effective information extraction. Two variable selection methods, Monte Carlo uninformative variable elimination (MCUVE) and variable combination population analysis (VCPA), are applied to select characteristic NIRS variables for the two fatty acids in camellia oil blends. Quantitative analysis models of the fatty acids are built using partial least-square regression. The results show that NWD1st-MSC preprocessing can be used for optimization of near-infrared spectra of the two fatty acids in camellia oil blends. It is found that the VCPA method can greatly improve the precision of the model and compress the modeling variables. For the oleic acid model, the modeling variables decrease from 1501 to 7, the root-mean-square error of cross-validation and correlation coefficient of calibration are 1.107 and 0.984, respectively, and the root-mean-square error and correlation coefficient of prediction are 1.178 and 0.981, respectively. For the linoleic acid model, the modeling variables decrease from 1501 to 8, the root-mean-square error of cross-validation and correlation coefficient of calibration are 0.089 and 0.987, respectively, and the root-mean-square error and correlation coefficient of prediction are 0.105 and 0.982, respectively. NIRS combined with NWD1st-MSC-VCPA-PLSR provides a quick and easy analysis method for measuring fatty acids in camellia oil blends.

Under gradually varying temperatures from liquid nitrogen temperature to room temperature, the spectroscopic characteristics of some typical natural diamonds after high temperature high pressure treatment and synthetic diamonds after high temperature high pressure or chemical vapor deposition processing are investigated by ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy and photoluminescence (PL) spectroscopy with 405 nm excitation source combined with Fourier transform infrared (FTIR) spectroscopy and DiamondViewTM. The results show that the directional feature absorptions in UV-Vis-NIR and PL spectra under different excitation light sources or test temperatures are not completely consistent with previous reports. These absorptions show clear temperature sensitivity, which attribute to the fingerprint and optimized feature absorptions. As the ambient temperature increases, the characteristic absorption peak intensity decreases gradually and some characteristic absorption peaks even disappear. The temperature-sensitive features of the diamond absorption spectra can provide important technical support and theoretical basis for the detection, screening, and characterization of diamonds, and also provide important reference for their new functional applications.

In order to effectively suppress the noise in gas detection and improve the inversion precision of gas concentration, we investigate a wavelet denoising algorithm for near-infrared broadband cavity-enhanced gas sensing system. Optimization analysis of wavelet denoising shows that it can achieve the optimal denoising effect by using db2 wavelet function as the wavelet base to perform 6-layer denoising on the polluted signal, and at the same time, by using heursure threshold estimation method and local threshold to zero the noise part wavelet coefficient. The near-infrared broadband cavity-enhanced absorption spectroscopy technique combined with a high-resolution Fourier transform infrared spectrometer is used to establish a gas sensing system for methane detection. The concentration inversion of methane absorption coefficient before and after wavelet denoising is performed using a least square fitting algorithm. Experimental results show that the inversed concentration results with wavelet denoising are closer to the true value than those without denoising. The inversion accuracy is improved by 7%, the signal-to-noise ratio is increased by 90%, and the system detection limit is reduced by 45%. It is evidenced that the wavelet denoising algorithm can effectively improve the detection accuracy.

Fourier transform spectrometry is an important device in spectral testing and analysis, which reconstructs a spectrum from a captured interference spectral signal. Invalid data points of the interference spectral signal, such as missing sampling points, oversaturation points, and noise points, arise from the photoelectric detection circuit’s instability and inadequate installation of interference module, and the recovery spectrum from an interference spectral signal containing such invalid data points causes distortion. Hence, a method for testing interference spectral signals is proposed using wavelet transforms, wherein invalid data points are quickly and effectively located, and a method for revising the interference spectral signal is researched based on interference signal characteristics of the interval where invalid data points are located. Spline interpolation is used for data fitting, and the interference spectral signal is revised accordingly. The feasibilities of both proposed methods are verified via simulation, and they are validated using a near-infrared Fourier transform spectrometer prototype. Thus, interference signals of the prototype are tested and revised to improve the accuracy of the recovery spectral signal.

In order to solve the problems of traditional characteristic spectral peak recognition and positioning methods, such as low recognition rate, large positioning error, and being unable to obtain spectral line-shape function, we propose a characteristic spectral peak recognition and positioning method based on an improved sine cosine algorithm. A sine cosine algorithm is improved by dynamic conversion probability, and then combines with the fitting methods of various spectral line-type functions (Gaussian, Lorentzian, and Voigt). The corresponding positions of characteristic spectral peaks can be obtained by iterative optimization. The improved method can not only locate characteristic peaks precisely, but can also obtain the line-type function of the spectrum. The experiments show that the proposed method significantly improves the recognition rate, positioning accuracy, peak fitting effect, and noise suppression ability for strong, weak, and overlapping peaks.

This study mainly investigates color constancy under RGB-LED light sources by visual psychophysics experiments. In the experiment, the subject is instructed to classify 240 Munsell surfaces under the neutral and four chromatic (red, green, blue, and yellow) illuminants produced by a RGB-LED lamp. The experimental results show that color constancy for each color category is relatively good when the light changes from the neutral to red and green, which is close to that of traditional broadband illuminants; color constancy for brown, red, yellow, and orange categories is bad when the light changes from the neutral to blue; color constancy for brown, red, and orange categories is bad when the light changes from the neutral to yellow. Overall, the color constancy under red and green illuminants is better than that under blue and yellow illuminants. These results can provide a reference for the design and application of RGB-LED light sources in practice.

A fringe reflection measurement system with simple structure is developed to measure the surface of an angel lobster eye X-ray lens, and it is easy to operate. First, a fringe reflection image of the lobster eye lens whose size is 40 mm×40 mm is taken by a charged coupled device camera, and the slope error distribution of the lens surface is calculated. The root mean square (RMS) and peak-to-valley (PV) values of the lobster lens obtained by the fringe reflection measurement system are 0.81 μm and 6.34 μm, respectively. The measurement results of the proposed system are consistent with those of the Zygo interferometer. The standard deviations of the RMS and PV values obtained by repeated surface measurements are 0.017 μm and 0.11 μm, respectively. The feasibility of the fringe reflection measurement system for measuring the surface of an angel lobster eye X-ray lens is verified. Then, the X-ray focus imaging simulation is performed for the measurement of the surface error of the lobster eye lens based on the Monte Carlo method. The full width at half maximum of the diffuse focal spot caused by the surface error is approximately 0.23 mm, and the corresponding angular resolution is 2.11'. This optical measurement system provides a reference for the spherical forming of the lobster eye lens.