For the concentration detection of particulate matter in the atmospheric environment, a Monte Carlo polarization scattering model was established on the basis of the Mie scattering theory, with the oil mist environment as the research object. The Stokes-Mueller matrix analysis method was employed to study the variation of Mueller matrix elements, and the patterns were investigated through Mueller matrix decomposition. Analyzing the Mueller matrix elements was an effective way of obtaining medium properties. Using the method based on oil mist concentration characterized by optical thickness, the model was proved correctly by experimental tests and simulations. The results indicate that with the increase in optical thickness (i.e., increase in concentration), the pattern of the Mueller matrix element M11 enlarges, and the non-polarized optical characteristics intensify. Moreover, the intensity value of the scattering depolarization matrix decomposed by the Mueller matrix goes up, and the scattering depolarization ability is enhanced. This method can distinguish the characteristics of particulate matter media at different concentrations more intuitively and achieve a visualization effect. It provides a theoretical basis and a new test method for the detection of atmospheric particulate matter concentration.

To tackle the low classification accuracy caused by the diversity and distribution complexity of surface objects in small-sample datasets of remote sensing image scenes, this paper proposes a transfer learning based mixture of experts (TLMoE) classification model. The model can achieve more accurate scene classification by taking full advantage of the features from the convolution layer containing the local details and the fully-connected layer containing the global information of scenes through multi-channels. First, a pre-judgment channel based on the fully-connected layer features is established to preliminarily judge all kinds of scenes with global scene information; then exclusive expert networks are trained for each kind of scenes via the expert channel, which can mine the key local details contained in the convolution layer features of all categories of scenes targetedly and extract the local features used to distinguish the subtle differences between similar scenes to complete fine-grained identification. Finally, combined with the pre-judged weight, the model realizes the scene classification considering the global and local differences. Experiments on small-sample datasets show that the proposed method can effectively identify confusing scenes and achieve good classification results.

Given the large structure size and low processing reproducibility of the interferometric tapered micro/nano fiber sensor, this paper proposed a non-adiabatic tapered micro/nano fiber sensing structure. First, the dependence of the sensing sensitivity of the interferometric tapered micro/nano fiber sensor on the waist diameter and the sensing characteristics of different parts was investigated according to the fiber mode theory. Then, mode control in the tapering process of the fiber under the non-adiabatic condition was studied. On this basis, a tapered micro/nano fiber sensor structure was designed and fabricated with a waist diameter of 3.1 μm and a taper waist length of 1.1 cm. Its detection sensitivity of low refractive indexes reached 90250 nm/RIU. This structure, with small size and high processing reproducibility, lays a foundation for miniaturization and integration of sensors and is expected to be used in fields such as biomedicine and environmental monitoring.

Fiber coils are generally evaluated from the aspect of their temperature performance with the full-temperature zero bias range after being connected to a fiber optic gyroscope system. However, the full-temperature zero bias range can only judge the temperature performance of fiber coils but is less effective to guide their applications. To address this problem, this paper proposes the concept of equivalent asymmetric length (EAL) of fiber coils and the way to evaluate their temperature performance based on it. With quantitative analysis, the paper determines the EAL test method and verifies the feasibility of evaluating fiber coils with EAL and the guiding effect of EAL on fiber coil applications. The results show that EAL is approximately linearly correlated with the full-temperature zero bias range, and the temperature performance of three fiber optic gyroscopes whose symmetry is tuned depending on EAL is improved significantly at a temperature change rate of 1 ℃/min or 2 ℃/min. This indicates that EAL is capable of both accurately estimating the temperature performance of fiber coils and guiding their applications.

We proposed a trench-nanopore assisted double-clad weakly coupled few-mode fiber to alleviate the crosstalk caused by the coupling of adjacent linearly polarized (LP) modes. First, the finite element method was employed to analyze the effects of the fiber parameters on the minimum effective refractive index difference (Δneff) between adjacent LP modes. Then, the fiber was optimized to support 14 LP modes and satisfy the weak coupling conditions. Finally, we analyzed the bending loss, effective mode field area, and differential mode group delay of the optical fiber. Simulation results show that a minimum Δneff of larger than 6×10 -4 among all LP modes over the C+L band can be achieved by introducing a nanopore with a 253 nm radius in the center of the fiber core. Meanwhile, the trench assistance structure added reduces the bending loss from 10 -3 dB/m to 10 -5 dB/m, thereby providing the fiber with favorable bending resistance. The fiber, with good transmission performance, has great application potential in short-distance large-capacity mode division multiplexing systems.

In order to realize the alternate detection of the in-phase and quadrature components of the signal, a coherent detection scheme based on a preset frequency offset is proposed in this paper. The hardware quantity required by this scheme is the same as that of heterodyne detection, which is half of that of homodyne detection. Relevant experiments and simulation results show that, compared with the heterodyne detection scheme. This scheme does not require a subsequent down-conversion process and has a lower bandwidth requirement for the receiver. In order to solve the signal distortion caused by dispersion, laser frequency offset and receiver bandwidth limitation in this scheme, an adaptive real-value equalization structure is proposed. It provides a low-cost and low-complexity solution for the application of coherent detection in cost-sensitive access networks.

Fiber Fabry-Perot tunable filter (FFP-TF) is one of the core components of the demodulation system of a fiber Bragg grating (FBG) sensor. Its stability is essential to demodulation accuracy improvement, and temperature drift is one of the key factors affecting its stability. Given the problem of the transmission wavelength drift of FFP-TF in a variable temperature environment, a temperature drift compensation method based on the integrated moving window is proposed in this paper. The nonlinear relationship between transmission wavelength and temperature is modeled by the least squares support vector machine, and a moving window is built in the training samples. Moreover, a weighted integration method of the compensation result of each moving window through the neural network is proposed to mine more process information of the training samples. The experimental results show that the maximum measurement error of demodulation is ±13.5 pm when the integrated moving window is not introduced, and that is ±0.82 pm after introducing the integrated moving window, which means the proposed method effectively improves the temperature stability of the tunable filter demodulation in fiber grating sensing.

Optical camera communication (OCC) is a new wireless optical communication technology,which uses the rolling shutter working mode of mobile phone camera to shoot fast flashing light emitting diode (LED), receives the stripe image separated by light and dark, and decodes and recovers the image to realize data communication. However, the fluctuation of gray value in the process of data transmission will affect the bit error rate (BER), transmission distance, and data rate in the process of communication. A new demodulation scheme of OCC signal is proposed. The adaptive image enhancement algorithm based on expansion corrosion is used to eliminate the overall fluctuation of gray value, and the expansion algorithm is used to eliminate the local fluctuation of gray value. It is comprehensively processed from the overall and local aspects to eliminate the fluctuation of gray value to the greatest extent and improve the accuracy of judgment, so as to improve the communication performance of the system. To verify the performance of the proposed scheme, BER under different transmission distance and data rate is evaluated. The experimental results show that the average BER of the proposed scheme is two orders of magnitude lower than that of the traditional signal demodulation algorithm.

An optimization algorithm combining limiting acceleration inertia feedback and an extended state observer was implemented in the closed-loop control loop to ensure the stability of the airborne laser communication platform to transient step response and optimize the platform’s ability to suppress various order disturbances in the loop. Considering the system disturbance response as the breakthrough perspective, the conventional acceleration inertia feedback algorithm was explained, and the I/O characteristics and disturbance suppression ability of the algorithm were studied. Problems were found in the practical application as indicated. Limiting algorithms and reduced-order extended state observer were individually incorporated to improve conventional acceleration inertia feedback algorithms by step. The performance analysis and character analysis of the improvement process were studied. The proposed optimization algorithm was verified by simulation processes and physical experiments. The experimental results show that when the platform steps at a speed of 70 (°)/s, the step overshoot of improved control loop is approximately 50% that of the proportion-integration-differentiation (PID) control loop. Compared to the stable accuracy of the PID control loop [198 μrad (root mean square (RMS)], when the platform performed spatial disturbance isolation of 5 (°)/Hz, the dynamic stability accuracy of the improved platform for beacon light improves to 14.28 μrad (RMS). Further, the disturbance isolation of the improved control loop has an optimized performance of 11.42 dB.

Energy spectrum computed tomography (CT) can use attenuated data of multiple different energy spectra to obtain narrow energy spectrum projection, which can improve the accuracy of the quantitative characterization of components. Based on the unknown X-ray energy spectrum, a blind CT separation algorithm is proposed to obtain the projection of narrow energy spectrum. First, the X-ray multi-energy spectrum forward model with material prior is established, which can provide energy direction for narrow energy spectrum projection. Second, according to the Poisson statistical characteristics of the measured data, the constrained optimization problem about the energy spectrum fitting coefficient vector and the thickness vector is constructed, and the block coordinate descent algorithm is used to solve the problem. The algorithm can be updated alternately between non-negative matrix factorization and Gaussian-Newton algorithm. The simulation and experimental results show that compared with the existing algorithms, the CT images decomposed by the proposed algorithm have fewer hardening artifacts and noises, and each decomposed projection image conforms to the characteristics of narrow energy spectrum projections, which can improve the accuracy of obtaining narrow energy spectrum projection.

Objectdetection methods based on deep learning are the current research focus of computer vision. However, when detecting small objects, existing detectors often suffer from missing detection. Every pixel of hyperspectral images contain the spectral information of small object materials. Therefore, they can provide additional support for improving the detection performance on small objects. However, the adjacent bands of hyperspectral images are highly correlated. It is thus necessary to select representative bands to reduce the computational redundancy. In response, this paper proposed a hyperspectral small object detection model, which used the radial basis activation function (RBAF) to carry out spectral screening and object detection. Specifically, in view of the band redundancy of hyperspectral images, an attention mechanism based on the RBAF was designed for spectral screening. As for the high texture fuzziness and low distinguishability against the background of small objects, the resolution of input images was reconstructed first. Then, a radial basis object output network (RBOON) based on the RBAF was constructed to enhance object classification. For model simplification, spectrum screening and resolution reconstruction were integrated into an attention-based resolution reconstruction network (ABRRN). With the combination of the ABRRN and RBOON, the detection model can screen the specific spectrum and suppress false alarms and thus improve the accuracy of small object detection. Hyperspectral small object detection experiments show that the proposed method improves the two detection accuracy criteria, namely AP50 and AP50:95, by 5.4% and 0.2%, respectively, which means it is better than other methods.

Photonics integrated interference imaging method is a far-field imaging method developed in recent years, which aims at high quality imaging and system flattening. It is expected to reduce the energy consumption, volume, and weight of the system can be reduced to 1/10~1/100 under the same resolution. However, the existing systems have sparse characteristics for high-frequency signal sampling. When inverse Fourier transform (IFT) is used to solve the object intensity distribution, Gibbs ringing artifact appears in the sharp edge of the restored observation target, thus affecting the image quality. In order to suppress artifacts, entropy prior is proposed and the entropy penalty characteristics are studied. The maximum entropy algorithm is designed by using entropy prior and combining with the characteristics of photonics integrated interference imaging. In order to verify the performance of the method, a multi-layer hierarchical aperture arrangement structure with better performance is used for simulation, and peak signal-to-noise ratio (PSNR), structural similarity coefficient (SSIM), and mean square error (MSE) are used as image quality evaluation methods. Simulation results show that the maximum entropy algorithm can eliminate the artifacts caused by high-frequency sparse sampling. For the images obviously affected by ringing, MSE and SSIM can be improved by more than 50%, and PSNR can be improved by more than 10%.

In this paper, a convolutional neural network is proposed to obtain high quality absolute phase from single frame composite images. The composite image used in the proposed method is the fringe image embedded with speckle. The convolutional neural network consists of two sub-networks, which use the fringe mode component and the speckle mode component in the composite image to solve and unfold the wrapping phase. In the process of phase unwrapping, the proposed method uses the pre-photographed composite image and its fringe order as auxiliary information to ensure the accuracy of phase unwrapping. Experimental results show that the proposed method can minimize the number of projected images by using single-frame composite images and obtain high precision absolute phase, which provides a feasible solution for 3D measurement in high precision dynamic scenes.

For measurement methods of heterogeneous deformation strain with digital image correlation (DIC) technology, the accuracy of the reconstructed strain is greatly affected by the manually selected parameters. Through error analysis of the partial least squares (PLS) method and the regularized polynomial smoothing (RPS) method, a DIC-based self-adaptive strain field calculation method is proposed in this paper to solve this problem. The method searches for the parameter combination with the minimum total error within the given parameter range and uses the optimal parameters to obtain a strain field with higher accuracy. The measurement result is slightly affected by the type of the deformation field. The simulation experiment results show that the calculation accuracy of the method is close to that of the PLS method at the optimal parameters. This research effectively solves the problem of selecting the optimal parameters of PLS and RPS methods.

When processing point cloud slicing data with multiple contour boundaries, the existing boundary point sorting algorithms have problems such as the inability to distinguish each boundary, generation of abnormal boundary polygons, and cross-sectional area calculation errors, which result in low volume measurement accuracy. Therefore, an improved point cloud slicing method that considers multiple contour boundary segmentation is proposed in this paper for high-accuracy volume measurement of irregular objects. In this method, the multiple boundaries are segmented by the segmentation based on euclidean clustering (SEC) method or the polygon splitting and recombination (PSR) method. Then, the inclusion relationships of the boundary polygons are clarified by the PNPoly algorithm, and the cross-sectional areas are calculated. Finally, the volume of the point cloud (that is, object volume) is calculated by accumulating the cross-sectional areas according to the slicing order. Multiple datasets are used to compare and analyze the effectiveness and correctness of the proposed two boundary segmentation methods as well as their volume measurement accuracy and efficiency. Experimental results demonstrate that the PSR method has high boundary segmentation accuracy, strong applicability, stable and reliable volume measurement accuracy (relative errors of volume calculation on three datasets are 0.0901%, 0.0557%, and 0.0289%, respectively), and less calculation time (with calculation time of 2.229 s, 33.732 s, and 327.476 s, respectively), thereby achieving the purpose of high-precision volume measurement.

The method of oil film thickness measurement based on ultraviolet-induced fluorescence technology has been widely used in wind tunnel oil flow tests. However, pose change of the model bearing the fluorescent oil film will affect the accuracy of oil film thickness measurement in dynamic wind tunnel tests. In the scene of primary illumination of ultraviolet excitation light source and direct imaging of oil film, the error in the imaging fluorescence intensity caused by the model pose change is analyzed theoretically and experimentally. The changes in the radiation characteristics, received fluorescence intensity, and imaging received fluorescence intensity of the model surface are investigated when the measured model is translated or tilted. The accuracy of oil film thickness measurement is represented by the error of the imaging fluorescence intensity. The analysis results show that the error in the oil film thickness measurement depends on the translation distance, and a longer translation distance results in a larger error when the model translates. The relative error of oil film thickness measurement is less than 1% when the model takes on a small-angle tilt (-4°--4°).

To overcome the difficulty in 3D shape measurement of dynamic isolated scenes, this paper proposed a method of temporal Fourier fringe analysis. The temporal modulation of the multi-period phase-shifted projection fringes by the measured dynamic scene was given full play in this study. On this basis, a temporal Fourier fringe analysis was carried out on these deformed fringes loaded with information of changes in the measured surface shape. Phase extraction was then conducted, and the corresponding 3D reconstruction of the dynamic isolated scene was achieved. The spatial high-frequency information of the complex scene was well retained by this method. Meanwhile, for the accuracy and reliability of the phase information, a disc grating of three-frequency composite fringes was designed. The grating, driven by a motor, began rotation projection, producing multi-period phase-shifted fringes on the measured scene surface. No spectrum filtering operation was performed in the spatial domain. Temporal phase unwrapping was carried out after the corresponding phase information was solved for the three-frequency fringes. The proposed method is suitable for isolated object measurement. Only one frame of a deformed fringe pattern is required for the retrieval of its corresponding 3D shape, so this method is applicable to dynamic scene measurement. Verification experiments were conducted on a newly developed measurement system. The results demonstrate the feasibility of the proposed method and system.

In order to meet the needs of rapid acquisition of morphological information in clinical testing and other fields, a fast three-dimensional morphological reconstruction algorithm requiring only two phase images is proposed. The algorithm obtains the structural boundary of the sample on the corresponding incident light orthographic projection plane from two orthogonal phase diagrams. By establishing and solving the correlation between the two groups of orthogonal two-dimensional data, the three-dimensional coordinates and average refractive index of the sample substructure contour are obtained, and then the quantitative distribution of the physical thickness of each substructure is given to realize the three-dimensional structure reconstruction of the sample. The three-dimensional shape reconstruction of samples with different structural characteristics is carried out through simulation and experiments. The experimental results verify the effectiveness and universality of the proposed algorithm.

A high-power multi-pass-pump Yb∶YAG planar waveguide laser amplifier was designed. The new amplifier adopted symmetrical pumping scheme, in which the pump sources were symmetrically placed on both sides of the planar waveguide. The pump light, reflected in the planar waveguide, passed through the core multiple times. Multi-pass pump was thereby achieved. The factors affecting the pump absorption characteristics were analyzed, and the relationships between the geometric parameters of the planar waveguide were determined. The planar waveguide structure was optimized. The pump absorption, temperature, and output amplification characteristics of the planar waveguide amplifier were analyzed by a laser amplification model. The results show that the designed multi-pass-pump planar waveguide amplifier has high pump absorption and optical-to-optical efficiencies. When the power of the injected seed light is 200 W and the pumping power is 10 kW, its maximum pump absorption efficiency is 96.8%, with a corresponding amplified output power of 7483 W and an optical-to-optical efficiency of 72.8%. Meanwhile, a good absorption uniformity makes the amplifier less affected by the heating effect, which is beneficial to obtaining high-quality beams.

The observation stage, on which the vision-based monitoring system is installed, experiences slight 6-degree-of-freedom (6-DOF) shaking when working for a long time. As a result, it brings great errors to the measurement results. Therefore, a linear solution method for micro-motion variations of the cameras was proposed. Micro 6-DOF pose variations of the cameras were then linearly calculated with a newly constructed model of two orthogonal cameras in fixed connection. Simulation verification shows that when the three Euler angles of the cameras are less than 30' and the three translation vectors are less than 10 mm, the proposed method delivers better solution accuracy, robustness, and computational efficiency than the typical monocular perspective-n-point (PnP) pose estimation algorithm. Meanwhile, outdoor experiments show that the proposed method better calibrates the measurement error caused by the micro-motion of the observation stage. The subsidence of the target point 44 m away from the observation stage was measured and the result shows that in the case of 6 control points, the average absolute measurement error after the pose variation of the stage is calibrated decreases to 0.2 mm, which verifies the effectiveness and practicability of the proposed method.

Aiming at the technical problems of existing unmanned aerial vehicle (UAV)-borne hyperspectral imagers, a compact visible near infrared imaging spectral system is designed. First, an imaging spectrometer and a plane array camera are integrated to design the common optical path. Then, the high frame frequency plane array image is used to invert the position and attitude parameters of the camera. Finally, the high-precision spatial information correction is carried out for the synchronously obtained push and sweep hyperspectral image. The system has a working range is 400--1000 nm, a field of view is 43.6° in the width direction, a field of view is 20.0° in the flight direction, a focal length is 13 mm, and a spectral resolution is better than 2.5 nm. ZEMAX software is used to optimize the design and analysis of the system, and prism-grating prism (PGP) design is used for the spectrometer, which has the characteristics of light weight, low cost, and high resource utilization.

Aiming at the quality of the light beam output by the silicon-based optical phased array chip affected by the phase noise during the waveguide etching and bonding process, a phase controller is developed based on the stochastic parallel gradient descent algorithm with a high-speed single-point photodetector as the performance evaluation function collector. Construct a one-dimensional 64-element silicon-based optical phased array chip beam optimization principle experimental system, and realize the fast phase noise compensation of silicon-based optical phased array chip. Then, we study the influence of the matching relationship between the performance of the phase controller and the response characteristics of the silicon-based optical phased array chip on the beam optimization effect, the influence of the initial light field intensity on the convergence time of the stochastic parallel gradient descent algorithm, and the influence of the ambient temperature on the phase noise compensation effect. The experimental results show that the time for the system to complete the single-angle beam optimization is 0.26 s, and the optimized beam indicators are consistent with the device design.

Caustic theory is a method of constructing the initial wavefront by using the tangent clusters of the light propagation trajectories. The surface wave designed and transmitted based on the caustic theory has the advantages of local field enhancement and controllable propagation trajectory, so it has important applications in optical microscopy, optical sensing, and control of light wave coupling. A method for designing the grating structure of Bloch surface wave excitation based on the caustic theory is proposed. Using bilinear grating structure for numerical simulation,a non-diffraction surface wave that can propagate 100 μm is realized, and the influence of the grating structure parameters on the coupling efficiency of the surface wave is analyzed. Furthermore, a simple grating structure is designed according to the caustic theory, which can realize the regulation of self-accelerating transmission of surface waves along any trajectory through simulation calculations. The results provide an effective way to manipulate the transmission of light waves at the sub-wavelength scale and the port design of on-chip optical interconnection.

In order to reduce the strong absorption of terahertz by water when detecting solution samples and improve sensitivity of sensor, we propose two dual-band terahertz sensors based on metamaterial absorber integrated microfluidic. The unit resonance structure of the two sensors is composed of metal ring and double I-type cross structure, which produces two perfect absorption peaks in the frequency range of 0.2--1.4 THz, and the refractive index sensitivity can reach 300 GHz/RIU. Experimental results show that the designed two dual-band terahertz sensors have polarization insensitivity and wide incident angle insensitivity, and keep good sensing performance within fabrication tolerance range -4%--4%, and have potential application in the field of biomedicine.

An optical fiber sensor based on metal-organic frameworks (MOFs) was designed and fabricated. It consisted of a section of no-core fibers (NCFs) spliced between two single-mode fibers (SMFs) and a ZIF-8 nanofilm coated on the surface of the NCFs with the in-situ crystallization. When an optical signal was coupled from SMFs into NCFs, a variety of high-order modes were excited and multimode interference took place. The interference result was exceptionally sensitive to changes in the refractive index of the environment surrounding the NCFs. The porosity of the ZIF-8 material and its specific adsorption ability for ethanol molecules were availed. The adsorbed ethanol molecules filled the pores of the ZIF-8 nanofilm, which resulted in changes in the refractive index of the nanofilm and the condition for multimode interference in the NCFs. Consequently, shifts in the transmission spectrum occurred. Trace ethanol in an aqueous solution was thereby detected. The experimental results show that the sensor has a sensitivity of 1.3 nm·% -1 and a lower detection limit of 1% (ethanol/aqueous solution, volume fraction). The proposed optical fiber sensor, with a simple structure and being easy to prepare, can be applied to the detection of trace organic molecules in water.

The GaoFen-7 satellite (GF-7) is the first 1:10,000 scale stereo satellite independently developed by China. The full-waveform laser altimeter and dual-linear array camera carried by the GF-7 provide a new way of establishing worldwide digital elevation models. The active and passive composite mapping function of the laser footprint and dual-linear array stereo image can be fulfilled when the position of the laser footprint in the dual-linear array stereo image is determined. To this end, the laser footprint camera monitoring the laser pointing needs to work simultaneously with the dual-linear array camera in the daytime to determine the laser spot position in the image coordinate system of the dual-linear array camera. Due to the operating characteristics of the laser footprint camera in the synchronous exposure mode, the spot image overlaps with those of ground objects or clouds. With strong background noise, either the spot center position obtained from an image captured by the laser footprint camera is poor in accuracy, or no spot center position is obtained. According to an analysis of multi-track images captured by the laser footprint camera, when the laser works continuously, the spot center shifts in the positive X direction with the increase in working time and presents linear characteristics that are affected by fluctuation of laser output energy. In contrast, it is stable in the Y direction. Piecewise linear fitting and data interpolation can be used to obtain the spot center position under strong background noise and thus to greatly improve the utilization efficiency of laser data. The variation law of laser pointing not only serves as a reference for later calibration and calculation of systematic errors in laser pointing but also provides a new idea for the analysis and processing of laser altimeter data in the future.

Metal nanoparticles possess the localized surface plasmon resonance (LSPR) effect and are widely utilized in the field of biological imaging due to their unique optical properties, easily controlled surface chemistry, and excellent biocompatibility. For the application of rotation-symmetrical gold nanoparticles (nanospheroid, nanocylinder, and nanorod) in biological imaging, the light backscattering properties of rotation-symmetrical gold nanoparticles were studied by using the T-matrix method and dielectric function size correction model. The optimal light backscattering properties and the corresponding optimal size parameters were obtained. Three typical excitation wavelengths (830, 840 and 900 nm) used in biological imaging were considered. The results show that the gold nanospheroid with an aspect ratio of 3.7 and a length of 146 nm has the optimal light backscattering properties at the incident light wavelength of 900 nm. In addition, the effects of incident light wavelength and tissue refractive index on the optimization results were analyzed. The results show that the volume backscattering coefficients and the size parameters of the optimized gold nanoparticles increase with the increase of incident light wavelength and decrease with the increase of tissue refractive index. Finally, the ranges of size parameters maintaining the volume backscattering coefficients greater than 90% of the maximum value were calculated. This study provides theoretical guidance for the application of three kinds of rotation-symmetrical gold nanoparticles in biological imaging.

Although fixed wavelength modulation spectroscopy has the advantage of high temporal resolution, a large measurement error of gas concentration appears with the wavenumber drift of the laser emission center. A gas concentration measurement method based on fixed wavelength modulation spectroscopy was proposed in this paper to eliminate the influence of wavenumber drift on concentration measurement. A reference optical path with a closed gas cell was introduced, and the wavenumber offset of the laser emission center was calculated according to the harmonic height. A cyclic iterative algorithm was adopted, and the gas concentration to be measured was calculated through inversion. A measurement system based on fixed wavelength modulation spectroscopy was built. The working temperature of the laser was adjusted to simulate wavenumber drift. The absorption line of CH4 molecules near 6046.955 cm -1 was selected to carry out concentration measurement experiments. The results show that the maximum relative error of concentration measurement is reduced from 90.510% to 5.204%. Errors smaller than 70.000% can be controlled within 2.000% after correction. This means that the proposed method can accurately calculate the wavenumber offset, improve the measurement accuracy of gas concentration, and thereby provide technical support for fast field inversion by fixed modulation spectroscopy.

Optical thin-film filters for multispectral palmprint image acquisition systems were designed. According to the different reflectance characteristics of palm skin in visible and near-infrared bands, we analyzed the spectral characteristic parameters and film design of palmprint recognition filters. For better quality of palmprint images obtained by the systems, a four-channel filter design scheme was adopted. The spectral characteristic parameters are required as follows: the central wavelengths λ1=470 nm, λ2=520 nm, λ3=630 nm, and λ4=880 nm. The full width at half maximum of each channel is 10 nm. The transmittance is higher than 90%, and the average cut-off background depth is greater than OD6 (spectral transmittance is less than 10 -6).

In this paper, 200 pairs of sphere samples (150 pairs of matte ones and 50 pairs of glossy ones) with a diameter of 4 cm were prepared by a Sailner J400 color three-dimensional (3D) printer to study the applicability of the existing International Commission on Illumination (CIE) color difference formulas (based on two-dimensional colors) to the color difference evaluation of 3D printed sphere models. The colors of these samples are distributed around five color centers (gray, red, yellow, green, and blue) recommended by the CIE. A total of 59 observers with normal color vision aged from 19 to 26 were organized to carry out color difference evaluation experiments by the gray scale method. Eight color difference formulas based on three color spaces, namely CIELAB, CIECAM02, and CAM16, were tested on performance and optimized with the methods of the power function and the lightness factor optimization. The results indicated that the original color difference formulas deliver relatively consistent predictions of the color differences of the 3D printed sphere samples, with a standardized residual sum of squares (STRESS) value of 32.5--34.7. The prediction performance on glossy sphere samples was better than that on matte sphere samples. The F test showed that the performance of the power function method of color difference calculation developed for 3D sphere samples was significantly improved compared with that of the original formulas, with an optimized STRESS value of 24.5--27.3. No significant improvement was observed after kL optimization.