This PDF file contains the front matter associated with SPIE Proceedings Volume 11566, including the Title Page, Copyright information, and Table of Contents.

Aerosol fine mode fraction (FMF) is an important parameter in associating aerosol loading with fine particle matter (PM2.5) pollution in the atmosphere. Previous studies have retrieved FMF from scalar measurements (centered at 490, 550, 670, 870, 1610 nm) from Synchronization Monitoring Atmospheric Corrector (SMAC) sensor. As a polarimetric instrument, SMAC also provides degree of linear polarization (DOLP) measurements (centered at 490, 670, 870, 1610 nm). In this paper, we try to evaluate the capabilities of both scalar and polarimetric measurements for aerosol retrieval. For the purpose, the analyses of information content and errors propagation are performed based on synthesized SMAC data. The Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) is adopted as the forward model, and the ground-based skylight measurements on the solar principal plane are simulated. Additionally, the analytic formula used to calculate Jacobians of DOLP with regard to FMF is verified by the finite difference method. Secondly, based on the information content analysis theory, the degree of freedom for signal (DFS) of FMF contained in polarimetric observations are calculated. Meanwhile, the a posteriori error of FMF are also calculated for the error propagation analysis. We found the mean DFS of FMF is greater than 0.8, which indicates that the FMF can be well retrieved from both intensity and polarization measurements. Compared to scalar measurements, the DOLP measurements can provide extra 0.14 and 0.08 DFS for fine- and coarse-dominated aerosols, respectively. As for the inversion errors, the uncertainties of both AOD and FMF decrease apparently. The a posteriori error of AOD decreases from 23.33% to 11.6%, and the a posteriori error of FMF decreases from 33.8% to 26.5%.

Sagnac interferometer is an important structure of lateral shearing interferometer. The shearing distance of the interferometer affects the measurement sensitivity of the interferometer and the stripe density of the fringes. A Sagnac interferometer with dove prism with variable lateral shearing distance is proposed. A dove prism is placed in the traditional optical path between the two mirrors in the Sagnac interferometer. The shearing distance of the interferometer can be adjusted by rotating the dove prism continuously. This structure can get the shearing distance over a wide range and reduce the influence of vibration on the system in the Sagnac interferometer during adjustment. The availability of this interferometer was confirmed after simulation and experiment.

Intraoperative diagnosis plays an essential role in cancer surgery by providing fast and accurate information to clinicians to make a decision. The standard workflow for histopathology based intraoperative diagnosis is generally considered to be time-consuming and labor-intensive. Fourier transform infrared (FTIR) vibration spectroscopy technique has been demonstrated to be a useful tool that yields a molecular fingerprint and provides rapid, nondestructive, high-throughput and clinically relevant diagnostic information. In this study, FTIR spectrometer based on synchrotron radiation was applied to collect the IR spectra of the liver cancer tissues and the adjacent non-cancer tissues of hepatocellular carcinoma (HCC) patients. The FTIR data demonstrated that the ratio of 2959/2926cm^-1, 1654/1548cm^-1, 1084/1548cm^-1 and 1455/1398cm^-1 had a significant difference between the two groups, which could serve as indicators to distinguish the liver cancer region from the adjacent non-cancer tissue. Then the supervised machine learning techniques including discriminant analysis coupled with principal component analysis (PCA-DA), support vector machines (SVM) and backpropagation neural networks (BPNN) were applied to classify the spectra data. Finally the performance of these models, such as their precision, sensitivity, specificity and accuracy was assessed, and the results have proved that coupling the FTIR vibration spectroscopy with supervised machine learning techniques could be considered as an accurate and efficient method for the intraoperative diagnosis of HCC.

Image restoration has attracted the attention of many scientists due to the image is degraded by the bad weather (such as haze, smog, fog). Clear images provide a means for security surveillance, remote sensing and various military application to understand objective facts. Many dehaze methods have been proposed by the experts for image restoration, especially for image dehaze. The dark channel prior dehaze method is a typical image restoration method based on atmospheric physical model. This method is a kind of statistics of outdoor haze-free images, and it is a simple but effective remove haze from a single input image. However, this method fails to restore the sky region of degraded image, and it has a high computational cost associated with soft matting algorithm. To overcome these problems, we propose an image restoration method based on quadtree decomposition to restore the images degraded by scattering media. The proposed method uses the quadtree decomposition to find the sky region for the atmospheric light estimation. The transmission of sky region is improved by the proposed method to obtain an accurate global transmission of degraded image. The degraded image can be quickly restored by our proposed method without halo effect or color distortion. The proposed method will be helpful to the security surveillance, remote sensing and various military application et al.

When using continuous frame space target images to perform space target detection, motion parameter estimation, and motion trajectory extraction, one problem that needs to be solved is the problem of entering and leaving the field of view of satellites and stars and other space targets. Detection is the basis of high-precision motion parameter estimation between frames. Use the STK EOIR module to generate space target sequence images. Based on the singular value decomposition theory, calculate the parameters such as the amount of rotation, translation, and scaling factors of the inter-frame image. The analysis of the inter-field parameters of the field of view identifies the points contained in and out of the field of view and detects them. The experimental results show that the algorithm is simple and fast, and can effectively detect space targets in and out of the field of view.

The main propose of this paper is to discuss the possibility of a space-based early warning technology for missiles in boost phase based on the near-infrared fine spectrum of potassium atoms in the exhaust plume. Emission transfer link from the exhaust plume to the detector is established in combination with the observation model of satellite and target on the ground. Line-by-line integral method is used to calculate the characteristic spectrum of potassium atoms. The result shows the potassium line have high spectral emissivity and narrow bandwidth. The analyses on the atmospheric transmission and background radiation indicate that the atmospheric transmission of the 769.896 nm potassium line is higher than that of the 766.490 nm potassium line which lies on top of an O₂ line, and the irradiance of the 769.896 nm line is stronger than that of background and the 766.490 nm line. Considering atmospheric transmission and background radiation, it is suitable to choose the 769.896 nm line to detect the exhaust plume of the missile. According to the characteristic of potassium atoms emission line with narrow bandwidth, a 1.2 nm wide filter centered on 770nm is used to extract target signal. The maximum detection range and other indexes are evaluated. The simulation results show that ultra-narrow band filter can achieve a large degree of background suppression, and the system performance indexes meet the detection requirements. Therefore, it is feasible that missile detection can be realized by using near-infrared fine spectrum of potassium atoms.

Traditional anomaly detection algorithms for hyperspectral imagery does not consider spatial information of imagery, which decreases detection efficiency of anomaly detection. The traditional RXD algorithm uses Gauss model to evaluate the distribution of background, but ignores spatial correlation of the imagery. Aiming at improving detection efficiency, this paper proposed an anomaly detection algorithm which utilize both spatial and spectral information of hyperspectral imagery based on graph Laplacian. In this paper, an anomaly detection algorithm for hyperspectral imagery based on graph Laplacian (Graph Laplacian Anomaly Detection with Mahalanobis distance, LADM) is presented. The spatial information is considered in the model by graph Laplacian matrix. First, LADM considers not only spectral information but also the spatial information by mapping image to a graph. Secondly, a symmetrical normalization Laplacian matrix is constructed for the graph with Mahalanobis distance. The operation eliminates interference among the nodes, which improves the accuracy of Laplacian matrix and improves the detection result. Thirdly, LADM detectors is constructed with graph Laplacian detection model. Lastly, anomaly detection model based on graph is given based on graph Laplacian and spectral vector of the pixels. A threshold value is given to judge whether the currently detection pixel is anomaly or not. Experiments for synthetic data and real hyperspectral image is proposed in this paper. The proposed algorithm is compared with three classical anomaly detection algorithms. ROC curves and AUC values are given for both synthetic data and real data in the paper. Experiments results show that LADM algorithm can improve the accuracy of anomaly detection for hyperspectral imagery, and reduced the false alarm rate.

The spectral emissivity of the surface of the selective radiation body changes with the change of wavelength. Selective infrared radiator is designed based on frequency selective surface theory. Selective radiators can be achieved using periodic structures, which has the peculiar electromagnetic properties, and has a good regulating effect on the transmission of electromagnetic wave by scientific and reasonable design. Using HFSS software, a frequency selection surface based on periodic single-screen ring was constructed. The ring was made of metallic gold, the dielectric layer was made of silicon dioxide, and the parameters of the basic unit were in the order of micron. The modulation characteristics of electromagnetic wave transmittance of the surface in the infrared band are calculated. It is found that the designed selective radiator has an emissivity of less than 0.1 in the 6.44-10 micrometer band. It is found that with the increase of the interval, the bandwidth of the low transmittance at the long wave becomes narrow. If the inside diameter of the ring is kept unchanged, the outside diameter of the ring is increased. As the width of the ring increases, the resonance frequency of the electromagnetic wave at the long wave decreases and the bandwidth of the low emissivity increases. As the width of the ring decreases, the resonance frequency of electromagnetic wave moves from high frequency to low frequency and the bandwidth of low emissivity decreases. Bandwidth with a transmittance of less than 10% varies from 17.6THz to 16.6 THz. Finally, the application of selective radiator is discussed.

Solar-induced chlorophyll fluorescence (SIF) is a weak optical signal emitted by chlorophyll under natural illumination. SIF ranges from 600 nm to 800 nm and is assumed as a direct proxy for actual photosynthesis. Due to recent advances in spectroscopy and retrieval techniques, SIF can be retrieved from hyperspectral remote sensing data. Statistical-based approach, typically the singular value decomposition (SVD) method, is one of the two practical strategies for SIF retrieval. A statistical-based approach collects SIF-free measurements of Fraunhofer Lines as training dataset, extracts their spectral features by a statistical approach and then applies the extracted features in the forward SIF retrieval model. In this paper, we first evaluated the performance of the SVD approach in SIF retrieval at proximal scale. Good consistency was found between diurnal SIF cycles given by the SVD method and a 3-FLD method, with SVD-based SIF values higher than those given by 3-FLD. We then applied the SVD method on HyPlant imaging spectroscopy airborne data. Spatial distribution of SIF was successfully depicted using the SVD method. SIF was in a good spatial accordance with NDVI, but the former exhibited a stronger heterogeneity. For both proximal and airborne scales, the in-filling of the Fraunhofer Lines by SIF was successfully detected by the SVD method. However, whether SVD could induce a systematic error should be further studied. It can be concluded that a statistical-based SIF retrieval method is a reasonable alternative to traditional O₂-lines-based methods, especially when synchronous SIF-free spectrum or pixelwise atmospheric correction is unavailable.

Solar spectral irradiance fluctuates periodically. MgII can describe solar activity and convert solar reference spectrum irradiance according to solar activity. In this paper, we first calculate the MgII, based on multiple solar spectra and construct a time-dependent MgII curve after considering the aggregation level of the curve. Then the error transfer formula of the MgII prediction value participating in the spectral time-varying calculation is derived. The requirement of absolute calibration accuracy is 3%, and the acceptable maximum prediction algorithm error need to below 2.24%. In the prediction algorithm, the Fourier first-class fitting is used for the principal components of the MgII curve, and the Fourier multi-class fitting is used for the high-frequency components. The order is determined by the fitting effect of the Fourier series at the end of the curve. Finally, MgII of the next 200 days and 3 years is predicted at 10 time points, and maximum average error between the true values and the predicted values is 1.863%(200 days) and 1.922%(3 years), which is less than the acceptable error of 2.24%. Predicting solar activity based on MgII is helpful for satellites to obtain accurate observation data.

A theoretical investigation into the nonlinear propagation and dispersive wave generation in the anomalous dispersion region of the highly nonlinear fiber (HNLF) is present here. Owe to the non-linearity of dispersive wave and four-wavemixing, by changing the parameter of input peak pulse, pulse width, initial chirp, and the parameter of HNLF, the optimum output in the short-wavelength region can be observed in the simulation results. It is found that the dispersive wave is mainly due to pulse trapping across the zero-dispersion wavelength (ZDW) by simulating the dispersive wave with different conditions. In the experiment, we can utilize the optimum parameter by the simulation to produce a high power pump source for difference frequency generation (DFG) method by 1550 nm near-infrared optical frequency comb. We have demonstrated a high pump power up to 12.5 mW coverage from 1025 to 1215 nm with a center wavelength of 1064 nm by choosing the HNLF with the dispersion of 4.933 ps/(nm • km) which is higher to the previous research. In our research, the simulation and experiment results are in good agreement in the article.

Hyperspectral Images (HSI) contains hundreds of spectral information, which provides detailed spectral information, has an inherent advantage in land cover classification. Benefiting from the previous studies on hyperspectral mechanisms, hyperspectral technology has achieved significant progress in classification. Deep learning technology, with remarkable learning ability, can better extract the spatial and spectral information of HIS, which is essential for classification. However, the research and application of deep learning in HIS classification are still insufficient, especially in terms of combining with prior knowledge, which has an advantage in data optimization. In this paper, a novel CNN network, name IUNet, is proposed for airborne hyperspectral classification. Besides, Besides, a series of knowledge-guided methods such as Radiation Consistency Correction (RCC) and Minimum Noise Fraction (MNF) were introduced to optimize the HIS data. Selected spectral indexes are employed to improve the classification accuracy according to the characteristics of the target. The HyMap images from Gongzhuling area of Jilin Province are used for experiments, and the experimental results show that the application of prior knowledge in data optimization can significantly improve the classification performance of hyperspectral classification based on deep learning.

Environment-2 (HJ-2) A/B satellites will be launched in 2020, which are expected to work as the successors of Environment-1 (HJ-1) satellites in Chinese Environment and Disaster Monitoring and Prediction Satellite Constellation. A new space-borne instrument called Polarized Scanning Atmospheric Corrector (PSAC) also will be onboard HJ-2 satellites, aiming to provide the atmospheric properties for synchronous atmospheric correction of the main sensors, such as the charge-coupled device cameras onboard the same satellite. PSAC is a cross-track scanning polarimeter with polarized channels from near-ultraviolet to shortwave infrared, centered in 410, 443, 555, 670, 865, 910, 1380, 1610 and 2250 nm. In order to test the performance of inversion algorithms and software modules, synthetic data simulated by the vector radiative transfer is indispensable. In this paper, the regional simulation of PSAC multispectral measurements are preliminarily studied, and the Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) has been used as the forward model. For the observation geometries, the viewing zenith angles are calculated by the linear interpolation over the cross-track scanning angle range from west to east, while the viewing azimuth angle are simulated by following the azimuth angle distribution of other corresponding satellite. By taking the vegetated surface type as an example, the multispectral Lambertian surface reflectance and wavelength-independent BPDF model are used in the forward simulation, and different aerosol optical depth with fine-dominated and coarse-dominated aerosols are considered. In this way, the multispectral measurements can be obtained by the forward simulations over a regional grid with the predefined latitude and longitude, and further analysis are carried out based on the synthetic data. Thus, this study can provide key support to the testbed of inversion algorithms and software modules before and after the satellite launch.

For the satellite remote sensing of aerosols in Ultraviolet (UV) wavelength bands, the atmospheric widow in UVA spectral bands from 315nm to 400nm are usually used. To derive the aerosols and surface reflectance from satellite UV measurements, a suitable radiative transfer model is indispensable for designed retrieval algorithms. In this study, we focus on the sensitivity study of polarization measurements in the UV wavelength bands, and Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) is used as the forward model for the simulation of the synthetic data. The hyperspectral surface reflectance of green vegetation and man-made materialsin UV have been extracted from the spectral library of John Hopkins University (JHU), and the polarized surface reflectance is also integrated in forward simulations. Both the fine-mode and coarse mode dominated aerosols are selected to investigate the influence on the measurements at the top of the atmosphere (TOA). For the separate contributions of Rayleigh scattering, aerosols scattering/absorption and surface-atmosphere coupled results, different input options are set in the UNL-VRTM. With the combination of gas absorption in forward simulation, the Rayleigh contribution, atmospheric path radiance and coupled contribution with surface are obtained, and the corresponding sensitivities are investigated and discussed. The results in this study can provide important support for the design of retrieval algorithms in UV.

Low size-of-source effect (SSE) infrared optical system design and experimental validation are critically involved. SSE is commonly explored in infrared radiation measurements. The main causes of SSE are the diffraction of the field aperture, the reflection of optical components and objective aberrations. The optical path design and the internal components scattering have an important influence on SSE. Reflective optical system is commonly used in infrared radiation measurements with high temperature region and wide wavelength range, which can eliminate chromatic aberration and reduce coma. A reflective infrared optical system is designed and built based on the high-temperature Fourier transform infrared (FTIR) spectrometer infrared radiation measurement facility at NIM. The ambient scattered radiation and the thermal effect of optical components are controlled via the water-cooled scattered radiation shielding bin and limitation apertures. Experimental validation of the SSE characteristics of the FTIR infrared optical system is carried out via the uniform blackbody radiation source at 500 °C and various sized apertures using the direct measurement method. The corresponding calculation model will be described in the paper. SSE on 3.9 μm is measured via the direct measurement method by using a standard reference blackbody with good temperature uniformity as the radiation source. The effect of reflection is reduced via the high emissivity coating on the apertures. The results show that the effect of the SSE on the FTIR measurement facility at the wavelength of 3.9 μm is less than 2×10^-4. Details and results of the infrared optical system SSE measurement will be reported in the paper. All measurements can be traceable to the National Standards of P. R. China.

Retrieval of SIF and related vegetation biophysical variables from the top-of-atmosphere (TOA) radiance data ensures the consistency of physical meaning between different parameters and avoids the uncertainties and errors caused by atmospheric correction propagate to surface reflectance. For complex nonlinear models, global sensitivity analysis is the first step for retrieving biophysical parameters, which can quantitatively analyze the sensitive and non-sensitive input parameters for a model output, and gains insights into retrievable variables. In order to simulate the TOA radiance data, based on the four-stream radiative transfer theory, the coupling between the atmosphere and the non-Lambertian surface is described through a combination of radiative transfer models those were used to represent soil, vegetation and the atmosphere. A modified version of the Sobol`s method was used to analysis. The results show that:(i) From 650 nm to 850 nm, leaf area index(LAI), leaf inclination distribution function (LIDFa), leaf chlorophyll content(Cab) and leaf dry matter content(Cdm) were the most sensitive parameters affecting the output variance of the model among 12 input parameters. On the other hand, senescent material (Cs), leaf structure parameter (N), fluorescence quantum efficiency (fqe) and soil moisture percentage (SMp) have weak influences on the output radiance. (ii)When the atmospheric visibility is high (i.e.50km), the sensitivities of TOA radiance sensitivities are similar to that of TOC reflectance for the most sensitive parameters. (iii)The viewing and illumination geometry has a significant influence on the NIR wavelengths.

The solar spectrum of 400-2500nm wavelength is mostly used in optical remote sensing satellite for land observation. In this spectrum, the radiation received in the view field of satellite dominated by reflecting solar energy. This work analyzed the radiation transferring model of atmospheric scattering and absorption theoretically and simulated the effects on optical remote sensing of aerosol and water vapor experimentally. The theoretical radiation models of atmosphere scattering and absorption have been analyzed; the influencing processes of atmosphere scattering and absorption for remote sensing imaging chain have been simulated by atmospheric radiation transferring model. This work gives the impact mechanisms of atmospheric scattering and absorbing processes by tracing the radiation in the transferring chain from sun to land-surface and to satellite. Simulation experiments of aerosol absorbing and scattering effects on atmosphere path radiance and scattering transmittance and the effect of water vapor absorption on atmosphere transmittance have been made, including analyzing the effects of aerosol and water vapor in typical wavelengths of land observing satellite with three typical atmosphere models (mid-latitude summer continental model, mid-latitude winter continental model and 1976 US standard model). The results indicate that: 1) atmosphere aerosol scattering mainly affects the visible (VIS) solar spectrum, the effects becoming greater as wavelength being shorter thus caused the most significant influence on deep blue and blue bands, less effect on NIR and nearly no impacts on SWIR bands with wavelength longer than 2200nm. The atmosphere path radiance in SWIR is less than 1% of VIS, and the atmosphere scattering transmittance in SWIR is more than 4 times of VIS as the aerosol optical depth (AOD) increasing from 0.05 to 2. 2) Water vapor absorption mainly affects longer wavelength radiation, i.e. the near infrared (NIR) and infrared (IR) spectrum. Unlike aerosol effects, water vapor has more complex function in IR spectrum, there are several strong water vapor absorption peaks and atmosphere windows in NIR and SWIR, and the sensitivity of different absorption peaks are varied with the changing of water vapor content. Five IR bands, 865nm, 940nm, 1240nm, 1380nm and 1860nm, are involved to study the effects of water vapor on atmosphere transmittance. The atmosphere transmittance decreases from 0.97 to 0.2 in 940nm and 1240, and from 0.6 to almost 0 in 1380nm and 1860nm as the water vapor content increasing from 0.05 to 4.2 g/cm2, and 865nm is almost independent on the varying of water vapor. Image quality assessment experiments are implemented to study the degradation to image quality of optical remote sensing satellite caused by atmosphere absorbing and scattering effects. In assessment experiments, image sharpness is chosen as the quality parameters. Based on the comparisons of different atmospheric compositions correction in wavelengths of blue (490nm), green (560nm), red (665nm), NIR (965nm) and SWIR (1380nm) images of Landsat-8, the results show that aerosol has greater decreasing on image sharpness of blue band than others, and water vapor mainly degrades the image sharpness of NIR and SWIR bands. The result of image quality assessment experiments has verified the theoretical analysis.

The objective of this paper was to evaluates the shifted excitation Raman difference spectroscopy at 784 nm and 785 nm excitation wavelength for the non-destructive identification of 70 lipsticks of different brands and Product line, overcoming the lipstick fluorescence problem reported by previous works using Raman techniques. Full Raman spectra were analyzed from the different samples, any sample was selected to test homogeneity of lipstick samples. The results of this paper demonstrate that the shifted excitation Raman difference spectroscopy can effectively suppress the interference of fluorescence compared to the general Raman spectra,in combination with multivariate methods,a new method for the identification of lipstick was established. The visual classification delivered a high value of discriminating power i.e. 100%. Cluster analysis provided 99.88% discriminating power combined with Principal component analysis. The results of this study demonstrated that the shifted excitation Raman difference spectroscopy supported by chemometric methods was a new method for the identification of lipstick samples.

Hepatocellular carcinoma is a serious threat to human health and life, so early diagnosis of hepatocellular carcinoma is particularly important. A new method based on FTIR spectroscopy and classification tree is proposed in this paper to develop a rapid and accurate diagnosis method for hepatocellular carcinoma. FTIR spectroscopy was firstly used to compare the spectra of hepatocellular carcinoma and normal tissues. The spectra of hepatocellular carcinoma and normal tissues have showed remarkable differences, which implied that the structure and compositions of hepatocellular carcinoma tissues have changed compared with those of normal tissues. 12 peak locations from both hepatocellular carcinoma tissues and normal tissues were analyzed and they had statistical differences by t test, or Wilcoxon rank test with a significance level of 0.05. Thus, peak locations were served as feature vectors for construction of diagnostic models based on classification tree. Diagnostic models based on classification tree were constructed and validated via a 10- fold cross validation method. The classification tree model based on Gdi split criterion achieved an accuracy of 99.24% for discrimination between hepatocellular carcinoma and normal tissue. The results demonstrated that FTIR spectroscopy combined with classification tree could be utilized for rapid and accurate diagnosis of hepatocellular carcinoma.

As a new type of conventional Raman spectroscopy(CRS) technology, spatially offset Raman spectroscopy(SORS) can acquire subsurface information of the multi-layered materials and realize the detection of concealed materials in nonmetallic opaque and translucent containers. In this paper, the spectrum of NaNO₃ powder in a red opaque plastic bottle and a brown translucent glass bottle were detected with a 785nm SORS detection system. According to comparison and analysis, the Raman signal and fluorescence of the surface opaque HDPE container and the surface translucent glass container were suppressed by SORS. The subsurface concealed NaNO₃ Raman spectrum peak was detected successfully.

Recent developments in the exploration of atomic spin instrumentation have enabled the atomic magnetometer to become the most effective detector of magnetic fields. The stability of temperature in alkali vapor cells is an important factor for ensuring the measurement accuracy of atomic magnetometers. The alkali vapor cell is usually heated to 80°C ∼ 190°C. During the heating process, although the heating system reaches a steady state, the temperature inside the alkali metal cell will still fluctuate, which will affect the accuracy of the device measurement. In this paper, K cells were simulated and analyzed by using the theory of atomic absorption spectroscopy theory. By the mathematical relationship models, the simulation analysis of the cell containing alkali vapor found that, within a small temperature fluctuation range (±1°C), the temperature fluctuation of the alkali vapor cell filled with buffer gas and the broadening parameter of the atomic absorption spectrum, as well as the frequency shift parameter all show a linear relationship. In order to facilitate the actual measurement, the relationship between the detection light intensity transmitted through the alkali metal cell and the temperature fluctuation inside the cell was also analyzed in this paper. Through simulation analysis, it is found that, within a small temperature fluctuation range (±1°C), the linear relationship between the detected light intensity transmitted through the alkali vapor cell and the temperature fluctuation inside the cell also exists.

THz transmission spectra of monosaccharide polycrystal were tested and analyzed based on terahertz time domain system and Fourier transformation infrared spectroscopy system. The characteristic absorption frequencies of of samples were acquired and their spectral results in two kinds THz systems were contrasted and discussed. Based on Density Functional Theory (DFT), Gaussian 09 molecule software and CASTEP crystal software were adopted to optimize samples structures and calculate their characteristic absorption frequencies. The simulation results are in better agreement with the experiment ones.

The spectral polarization imager can detect the spectral polarization information of the target reflection or radiated light that cannot be obtained by ordinary optical instruments. The obtained spectral polarization image can provide richer target information than the intensity image and the spectral image. At the same time, being able to achieve snapshot imaging and improve the spectral resolution is the research and development direction of polarization spectrum imaging technology. In this paper, we present a dual channel snapshot compressive spectral polarization imaging technique for simultaneous acquisition of two-dimensional intensity information, one-dimensional spectral information, and four-dimensional polarization information of a target in visible range. One channel is based on a coded mask and micro-polarizer array, and one channel is based on a pixel-level polarizer array detector. The main optical path replaces the ordinary detector with a micro-polarizer array based on CASSI. The micro-polarizer array consists of 0°, 45°, 90°, and 135° linear micro-polarizers regularly distributed, and each pixel matches the pixel of the detector. The three Stokes parameters of the scene are compressed and sensed, and a four-dimensional (4D) data cube is projected onto a two-dimensional (2D) focal plane. Through nonlinear optimization with sparsity constraints, a 4D spectral polarization data cube is reconstructed from 2D measurements. The addition of a pixel-level polarizer array detector helps to improve the measurement accuracy of spectral information and polarization information. Optical experimental results confirm that the architecture reduces the total number of measurements required to obtain a spectrally polarized image compared to traditional acquisition methods. The dual channel combination enables simultaneous acquisition of spectral and polarization information, and improves the quality of reconstructed image based on compressed sensing algorithm. A dual-channel experimental device with coded aperture spectral polarization imaging channel and polarization imaging channel was set up to obtain spectral data cubes with 4 polarization states in 25 bands in the range of 450nm-650nm, and the polarization degree and polarization angle of each band. The spectral resolution was better than 10nm, and the spectral restoration accuracy was about 86.3%. Compared with the single-channel imaging method, the spectral reconstruction accuracy was improved by 10.5%.This has guiding significance for the design and research of light and miniaturized hyperspectral polarization imagers in the future. It is expected to be widely used in astronomical observation, atmospheric detection, biomedical diagnosis, earth environment monitoring, target detection and identification and other fields.

Incoherent strong light beams have been widely used in military, anti-terrorism and anti-drug fields. The transmission of the light beam in the atmosphere is affected by the absorption of the atmosphere, the scattering and refraction of particles in the atmosphere, so that the energy of the strong light beam is continuously attenuated during the transmission process. In order to study the atmospheric transmission characteristics of incoherent strong light beams under different conditions, a theoretical model for the transmission of incoherent strong light in the atmosphere was established, and the Modtran model was used to simulate and calculate the visible light atmospheric transmittance under different visibility conditions. On this basis, the illuminance of the incoherent strong beam after the attenuation of different atmospheric distances is further calculated. The results show that as the visibility decreases, the atmospheric transmittance decreases rapidly, and the illumination of the incoherent strong beam is greatly attenuated. The research results can provide some theoretical support for the in-depth application of incoherent strong beams in military and anti-terrorism fields.

Spatial heterodyne spectroscopy for long-wave infrared identifies an ozone line near 1133 cm^-1 (about 8.8 μm) as a suitable target line, the Doppler shifts of which are used to retrieve stratosphere wind and ozone concentration. The basic principle of Spatial Heterodyne Spectroscopy (SHS) is elaborated. Theoretical analyses for the optical parameters of spatial heterodyne spectroscopy are deduced. The optical system is designed to work at 160 K and to maximize the field of view (FOV). The optical design and simulation is carried on to fulfill the requirement. The principle prototype was built and a frequency-stable laser was used to conduct the experiment. Result shows that the designed interferometer can meet the requirement of spectral resolution (0.1 cm^-1 ) and that the spatial frequency of fringe pattern is consistent with the theoretical value at normal temperature and pressure.

Compared with the arrayed waveguide grating (AWG) that widely used as optical wavelength multiplexers and/or demultiplexers (MUX/DMUX) in optical communication networks, AWG of low diffraction order has enormous potential of application in cases that need a large free spectrum range (FSR), to name a few, various integrated optical spectrometer, and wavelength MUX/DMUX in coarse wavelength division multiplexing (CWDM) networks. In the current paper, an investigation is conducted on S-shaped antisymmetric design scheme for low diffraction order AWG layouting. To reduce overall AWG device dimension and increase bend waveguide curvature radius uniformity, particle swarm optimization (PSO) with constrained conditions is employed to find optimized geometrical parameters which determine AWG structure. PSO algorithm could reduce by about 50.6% of the AWG dimension compared with previously reported AWG and thus PSO could be a promising optimization method when designing AWG.

The conventional diffractive optical imaging spectrometer uses the single-channel scheme, it is mainly aimed at simple targets, or gas targets with known spectral characteristics. The main disadvantage of conventional system is: if the target is a complex scene such as a natural scene, it's very difficult to demodulate spectral images accurately. Because, the focused and defocused spectral information are superimposed on each other. And, the real system has noise, manufacturing error, testing error and calibration error. So, it is difficult to correctly describe the dispersion parameters of the diffractive spectrometer, which will cause large errors of spectral demodulation accuracy. To solve this problem, an efficient system of diffractive spectral imaging is discussed, which includes a reference channel. Based on the conventional single-channel system, a grayscale camera or a color camera is added for imaging. It can provide a priori knowledge of complex scenes for the diffraction imaging channel. The data of the two channels are jointly processed to improve the final demodulation accuracy of the spectral data. The system composition and basic principles are introduced, the performance of the system is analyzed. The virtual simulation experiment of diffractive optic imaging is established. The simulation of diffractive imaging and spectral demodulation of complex scene have been finished. The demodulation output images are almost the same as the original input image. The experiment system of diffractive optic imaging in visible band is also established in the laboratory. Theoretical analysis, imaging simulation and imaging experiment have verified the validity and feasibility of the diffraction imaging system with reference channel. Compared with the single channel system, the spectral demodulation effect is obviously improved, which greatly improves the application potential and application value.

Based on the working mechanism and characteristics of spaceborne hyperspectral Fourier transform infrared spectrometer, the computer and software were used as data acquisition and processing tools in this paper to study and simulate the various processes in photoelectric information processing of spectrometer. Analytical models including functional modules such as interference signal generation, effective signal detection, spectral data inversion and instrument error correction was established, then a visualization software system was developed. Finally, the accuracy of the model was calculated and optimized with experiments, the verification results show that this resolving system can process the interference data with high spectral resolution non-destructively, significantly improve the smoothness of the restored spectrum without distortion, and the measured spectral resolution of an instrument is better than 0.03cm^-1 . This digital model could provide useful support for the design and parameter optimization of the aerospace Fourier transform infrared spectrometer.

Laser heating of alkali metal vapor cells of atomic magnetometers is applied owing to its none magnetic field interference and little energy consumption, compared to heating by hot air and heating by AC electrical current. The development of laser heating technology, including the attachment of optical filters for better heat absorption, has expanded its usage from small chip-scale cells to relatively large cells, and from heating of single magnetometer to heating of an array of magnetometers. This paper offers a review of the evolution of laser heating in atomic magnetometers, introduces the different configurations of laser heating in experiments and points out the next possible target of the application of laser heating.

Stimulated emission depletion (STED) microscopy enables visualization of previously indiscernible subcellular structures in biological cells. However, it is costly and complicated to built a STED microscope system because of the dependence on the depletion laser, especially in multicolor imaging. In addition, inefficient fluorescence inhibition on account of the small stimulated emission cross-section results in a huge demand for the power of the depletion laser, which hinders its application to study living cells. Here we present a method based on phasor plot analysis for achieving two-color STED imaging at a relatively low depletion power, which is implemented in a pulsed-STED microscope system with only a pair of excitation and depletion laser beams. Firstly, two fluorescent dyes with similar spectral characteristics but different lifetimes were selected for two-color imaging. Secondly, a depletion laser with a wavelength closer to the emission maximum was applied to boost the depletion efficiency and reduce the required depletion power. This approach makes two-color STED imaging easier and has the potential to realize multi-color STED super-resolution imaging without the need of additional lasers, thereby offering more convenient and efficient service to researchers.

In this study, the combined effect of multiple factors on the photoacoustic detection of glucose solution was studied by using the artificial neural networks. These multiple factors include the excitation energy, temperature, flow velocity, and glucose concentration. To achieve the aim, a set of photoacoustic detection system of glucose solutions was established by using the OPO pulsed laser, ultrasonic transducer, the solution cycling sub-system, signal pre-processing circuit, data acquisition and controlling system. The peak-to-peak values of glucose solutions with different concentrations, temperatures, flow velocities under different energies of pulsed laser were all obtained by the orthogonal experiments. To get the relationship between the peak-to-peak values of glucose and the multiple factors, as well as between the glucose concentration prediction and the multiple factors, four different artificial neural network (ANN) algorithms, i.e., forward propagation (FP), radial basis function (RBF), back propagation (BP), and recurrent neural network (RNN) were used. The root-mean-square error(RMSE) values of different ANN algorithms for the peak-to-peak values prediction and the glucose concentrations prediction were all obtained and compared. Results show that the concentration prediction effect of RBF-ANN is better than that of RNN, BP-ANN, and FP-ANN. Then, to further verify the concentration prediction performance of RBF-ANN, the RMSE values for RBF-ANN algorithm under different parameters of spread were adjusted and compared. Results show that when spread value is 0.7, the RMSE values of photoacoustic peak-to-peak value and the glucose concentration are lest. When the neurons is 108, spread parameter is 0.7, the RMSE of glucose concentration is about 0.45mg/dl.

In recent years, the number of patients with hypertension has increased. Hypertension is an invisible killer. Long-term hypertension can cause a series of cardiovascular diseases such as angina pectoris, stroke, and heart failure. Therefore, early evaluation and grade assessment of blood pressure (BP) are essential to human health. The seventh report of the National Joint Committee for the Prevention, Detection, Evaluation, and Treatment of Hypertension in the United States (JNC7) classified BP levels into normotension (NT), prehypertension (PHT) and hypertension (HT). In this paper, we adopted a deep learning model (ResNet18) based on the ensemble empirical mode decomposition (EEMD) and the Hilbert Transform (HT) to predict the risk level of BP only using photoplethysmography (PPG) signals. We collected 582 data records from the Multiparameter Intelligent Monitoring in Intensive Care database (MIMIC), and each file contained arterial BP signals as the labels for inputs and the corresponding PPG signals as the inputs. Besides, the last fully connected layer of the model was initialized. We conducted three classification experiments: HT vs. NT, HT vs. PHT, and (HT + PHT) vs. NT, the F1 score of these three classification experiments is 88.03%, 70.94%, and 84.88%, respectively. A quick and accessible noninvasive BP evaluation method was offered to low- and middle-income countries.

Various forms of light therapy have been practiced around the world for many years. Among them the laser therapy has experienced a prosperous development in recent years. More and more laser equipment has been used in this field. In this study, we present an optical pumped vertical external cavity surface emitting laser (OP-VECSEL) system using semiconductor gain chip as the lasering material. Through carefully design of the semiconductor gain chip structure, the fundamental and frequency doubled laser emitting wavelength can be set to the range of 1040-1160nm and 520nm-580nm which is the mainly laser-tissue interact wavelength range for laser therapy. In a flat concave short cavity laser assembly test, the maximum fundamental frequency output power of the system is 1.6W using a 2% output coupler. Through a frequency doubling crystal, the continuous output power of the yellow green light can achieve 24mW.

In this paper, we use imaging photoplethysmography (IPPG) to realize non-contact measurement of blood volume change of human fingertip, which can avoid distortion of blood vessel wall caused by pressure applied to fingertip. We use CMOS color camera to collect signals and white LED as light source. In the process of signal processing, we abandon the traditional morphological filtering algorithm in the form of double-layer cascade, and use single-layer morphological filtering algorithm. Experiments show that the single-layer morphological filtering algorithm has a good effect of eliminating baseline drift of signals, and can perfectly retain the detail components of signals without shifting the transverse components. We proposed a peak-to-valley value detection algorithm to calculate the heart rate by detecting the time interval between the adjacent peaks value. The experiment compared the accuracy of calculating the heart rate by using the traditional fast Fourier transform and the heart rate based on peak-to-valley value detection. The respiration rate was detected by using the third-order Butterworth filter. The accuracy of heart rate monitoring can be achieved at 97.86% and the accuracy of respiration monitoring can be achieved at 95.02%.

We proposed and experimentally demonstrated a metal coated tilted fiber grating (TFG) for calmodulin detection. The sensor was designed as a reflective probe type by depositing a gold mirror in the down-stream of the TFG. A 50-nmthick gold nanocoating was radio-frequency magnetron sputtered over the fiber surface of an 18° TFG, and the transient receptor potential channels were bond onto the metal surface for calmodulin detection. The experimental results demonstrated that our biosensor can detect calmodulin with concentration as low as 1 μM. This result was better than that obtained using the isothermal titration calorimetry method. In addition, with the use of a custom-designed microfluid system, the volume of sample solution required by our biosensor was only 20 μL. Our proposed sensor is simple to fabricate and easy to implement, and it can be used for rapid, label-free, and microliter-volume biomolecule detection

Vitamin D is a group of fat-soluble secosteroids for increasing intestinal absorption of calcium, magnesium, and phosphate, and is related with other biological effects. The most important compounds of vitamin D for humans are vitamin D₂ (ergocalciferol) and vitamin D₃ (cholecalciferol), both of which can be ingested from the diet and supplements. The present study aimed to provide the optimized selection in power density and beam type for this problem. The light-emitting diode (LED) source with a peak wavelength of 284 nm was used to illuminate 7-DHC in different power density and beam type, and then the conversion rate was tested based on high performance liquid chromatography (HPLC). The used irradiated conditions include the 5, 10, 15 and 20 mW/cm2 , the used frequency includes 0.1, 1, 10 and 100 Hz, and the duty cycle includes 20%, 40%, 60% and 80%. Our results show that there is no obvious difference between the different irradiation for the used continuous light with the same dose of 200mJ/cm2 , but the conversion rate of pulse light source increases with the increasing of power density. Besides, compared with the continuous light source, the pulse light source has no better conversion effect. The conversion rate decreases with the increasing of pulse frequency from 1 Hz to 100 Hz. Moreover, duty cycle does not affect conversion rate for 7-DHC to previtamin D3. Only If the irradiation is altered, the conversion rate against to duty cycle will be changed. The power density indirectly affects the conversion rate through penetration depth, and the continuous illumination mode is better than the pulse illumination mode. This paper can help to up-regulate serum vitamin D level to patients with fat malabsorption syndromes as well as patients with other metabolic and hence to stimulate the application of artificial light sources like LED in health care.

Optical endomicroscope via fiber bundles has been widely used to provide cellular-level visualization for clinical applications. However, improving the quality and spatial resolution of the under-sampling images obtained by fiber bundle with the inter-core spacing remains a challenging problem. In this paper, we address the problem of deconvolution and restoration in fiber-bundle-based imaging. We propose a fast iterative shrinkage-thresholding algorithm (FISTA) solve this problem, and a high-resolution (HR) image without honeycomb patterns is restored from a low-resolution (LR) fiber bundle image. The feasibility of this mothed is verified by experimental results, which shows a promising and wide applications for fiber bundle imaging.

Coherent anti-Stokes Raman scattering (CARS) can be used to excite vibrational bonds with chemical selectivity, high spatial and spectral resolution, and high sensitivity, which has many applications in biomedical research. The common way to realize CARS imaging is illuminating sample with two synchronized ultra-short pulses. Recent development of various fiber laser schemes based on nonlinear optical effect provides compact laser source for CARS imaging. However, the nonlinear conversion in optical fiber may inevitably introduce temporal or spectral noise to the newly generated pulses. In this paper, we have proposed a polarization-maintaining (PM) passive-synchronized picosecond fiber laser system that generates dual-color picosecond pulses for CARS. An Er-doped fiber laser and a Yb-doped fiber laser were passively synchronized by cross phase modulation based on master-slave injection scheme. In the experiment, the wavelength of one branch was fixed at 791 nm, which was generated by second harmonic generation of Er-doped fiber laser. The wavelength of the other branch can be continuously tuned from 1017-1047 nm, which was obtained by adding an active spectral broadening module and an optical bandpass filter after Yb-doped fiber laser. As a result, the laser source allows to probe vibrational bonds with frequencies difference between 2809 cm^-1 and 3091 cm^-1 . Finally, the achieved tunable synchronized pulses enabled us to microscopically image mouse ear samples. The compact optical fiber laser proposed with PM fiber design, stable synchronization and large wavelength tunability would become a promising laser source for CARS imaging in clinical use.

Conventional flow cytometry has been used for leukemia characterization via fluorescence measurements. Here we measured the 2D light scattering patterns of label-free HL-60 cells (human acute myeloid leukemic cells) and K562 cells (human chronic myeloid leukemic cells) with a light-sheet illuminated flow cytometer. Approximately 70 light scattering patterns of leukemia cells were obtained in a one minute video taken by this cytometer operating at 50 frames per second. Local binary pattern (LBP) was used to extract features of the 2D light scattering images, which were then analyzed by the support vector machine (SVM) algorithm. An accuracy rate of 98.23% was obtained for the label-free classification of these two kinds of leukemia cells, with a specificity of 99.28% and a sensitivity of 97.22%. The combination of light-sheet flow cytometry with machine learning may be helpful for leukemia subtyping diagnosis in clinics.

In general, most of the adaptive optical systems for human eye aberration detection are based on the wavefront slope measurement provided by the Shark-Hartman wavefront sensor (SHWS), and then the wavefront slope is fed back to the deformable mirror to correct the human eye aberrations. Compared with the SHWS, the pyramid wavefront sensor (PWS) has the characteristics of fast sampling speed, wide linear capture range, and high sensitivity. Our works show that the modulation angle of the dynamic high-frequency modulator affects the dynamic measurement range, linearity and sensitivity of the pyramid sensing. The dynamic measurement range and the linear fitting residuals are both proportional to the modulation angle, and the sensitivity is inversely proportional to the modulation angle. Pixel combination affects the sensitivity of the detection signals of the pyramid sensor. The pixel combination mode of 1 × 1, 2 × 2, and 3 × 3 is tested respectively. When the pixel combination mode of 2 × 2 is used, the sensitivity of the signals will be highest significantly. In addition, the beacon light used to detect the human eye should not be too strong. The grinding “blind zone” of the spires and edges will have a scattering effect on the incident light and cause loss of light energy. Therefore, it is necessary to optimize the parameters of the pyramid sensor and further improve the processing technology of the pyramid prism.