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2021 Vol. 43, No. 7

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Materials & Devices
Effect of in-Situ Post-annealing on the Second Phase Inclusion Defects
YUAN Shouzhang, ZHAO Wen, KONG Jincheng, WANG Jingyu, JIANG Jun, ZHAO Zenglin, JI Rongbin
2021, 43(7): 615-621.
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Second-phase-inclusion defects in Bridgman-grown CdZnTe crystals were decreased via post-growth in-situ annealing combined with excess Cd in CdZnTe ingots. Based on the formation mechanism of the second-phase-inclusion defects in Bridgman-grown CdZnTe, the relationship between second-phase-inclusion defects and annealing temperature was studied. The size of second-phase-inclusion defects was reduced to less than 10 μm and their density to less than 250 cm-2 in CdZnTe at an optimized in-situ post-annealing temperature.
Investigation of Energy Band Structures of InAs/GaSb and M Structure Superlattices
LI Junbin, LIU Aiming, JIANG Zhi, KONG Jincheng, LI Dongsheng, LI Yanhui, ZHOU Xuchang, YANG Wen
2021, 43(7): 622-628.
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In this study, the band structures of conventional InAs/GaSb and M structure super lattices are investigated using the k·p method. First, the band structures of InAs/GaSb super lattices with various period thickness are calculated, and the period structure used for a longwave super lattice detector is obtained. Subsequently, the band structure of the M structure super lattice, which is prevalently employed in longwave super lattice infrared detectors, is also calculated. The band offset between a longwave InAs/GaSb super lattice and M structure super lattice is provided. Furthermore, based on the band structures, the relationship between the carrier density (doping density) and the position of the Fermi level for longwave InAs/GaSb and M structure super lattices is obtained. This was followed by a density of states (DOS) calculation. These calculated material parameters can provide the foundation for designing super lattice infrared detectors.
Systems & Designs
Multi-Channel Laser Automatic Control System Based on Closed-Loop Control
ZHANG Shufang, LIU Jiang, WU Jianjun, ZHANG Tao, FENG Zhaochi
2021, 43(7): 629-634.
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An automation control system for the optical path is proposed in this paper, based on the MC9S12XEP100 core controller, to realize automatic control of the optical path of the laser Raman spectrometer. A closed-loop control algorithm based on the pressure sensor is proposed to address problems such as low precision, easy "lost step, " and "blocked rotor" in open-loop motor control. This algorithm greatly improves the control accuracy and system stability and effectively avoids the problem of motor blocking. Experimental results show that the control system can realize the functions of arbitrary adjustment of multi-path light, access and reset of light path, closed-loop self-check, and host computer communication. The displacement error accuracy controlled by this system is within 0.1mm, which meets the basic requirements of stability, reliability, high precision, and strong anti-interference ability in the optical path control system.
Fast Spectral Acquisition Method Based on Compressed Sensing for Liquid Crystal Tunable Filters
SUN Zhishen, ZHANG Xu, WANG Suhui, CAO Yingying, GUO Tengxiao, CAO Shuya
2021, 43(7): 635-642.
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To improve the spectral acquisition efficiency of the Liquid Crystal Tunable Filter(LCTF). A fast acquisition method which could be applied to the spectral imaging system was proposed. A better observation matrix was designed and constructed. Within the theoretical framework of compressed sensing, spectral super-resolution reconstruction was made possible and the feasibility of the method was verified by experiments. The results indicated that when the sampling rate of was 18.08% (sampling step length was 30 nm), the correlation coefficient between the reconstructed 4.81 nm resolution spectrum and the traditional full sampling spectrum was 0.91, the Peak Signal-to-Noise Ratio (PSNR) of the reconstructed super resolution spectrum was 99.63 dB and the acquisition speed was 5.53 times that of the traditional method. As long as the quality of spectral recognition is ensured, this method can facilitate fast and lightweight acquisition of spectral information, which can technologically contribute to dynamic target measurement and rapid detection while improving the applicability of LCTF spectral imaging technology.
Disturbance Suppression Method of the Fast Steering Mirror on Space-based Platforms
LI Jinpeng, AI Zhiwei, BIN Yuan, LI Jing
2021, 43(7): 643-648.
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The effects of ionizing radiation and celestial perturbation force can cause current and position disturbances in the voice coil motor (VCM) and motion loader of the fast steering mirror (FSM) system on a space-based platform, which can affect the steady-state accuracy and tracking accuracy. To reduce the influence of disturbance, disturbance observations (DOBs) are introduced into the current and position paths to realize the suppression of specific disturbances. First, the influence of output accuracy caused by disturbances in a space-based environment are analyzed. Then, DOBs are introduced into the current and position output paths. The new systems are analyzed, and the disturbance controllers are designed. Finally, the theoretical data are simulated and compared with the test results of the rigid–flexible coupling virtual prototype control system. The results show that under the effect of dual DOB control, the disturbance suppression ability is 92.59% at 200Hz current and 40Hz position disturbance frequency. The error between the virtual prototype test results and the theoretical calculation result is within 10%.
Image Processing and Simulation
RPCA Infrared Small Target Detection Based on Local Entropy Reference in Preprocessing
XUE Xirui, HUANG Shucai, MA Jiashun, LI Ning
2021, 43(7): 649-657.
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Based on the non-local similarity of images, the use of image block recombination to obtain low-rank block images is the basic method for applying robust principal component analysis (RPCA) for infrared small target detection involving single-frame image. This paper introduces the process of applying the RPCA algorithm in infrared small target detection involving single-frame images and analyzes the influence of various blocking methods under different image backgrounds. To address the difficulty of selecting the image block window and sliding step size under a complex background, a selection method based on the larger value of the minimum local entropy of the image block is proposed. The experimental results show that by calculating the block local entropy of the image, taking the larger value of the minimum local entropy as a reference, and selecting the RPCA algorithm preprocessing scheme, better results can be achieved in the detection of small targets in a single frame of infrared images. This addresses the lack of experience of engineering personnel with regard to the application of the RPCA algorithm.
Real-Time Pedestrian Detection Based on the Weak Saliency Map in Thermal Infrared Images
LI Chuandong, XU Wangming, WU Shiqian
2021, 43(7): 658-664.
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To address the low precision and speed of existing pedestrian detection methods for thermal infrared images, a real-time pedestrian detection method based on a weak saliency map is herein proposed. The proposed method comprises two improved networks, namely, SD-LFFD and SF-LFFD, which use lightweight LFFD as the basic network. First, the thermal infrared image is input into the SD-LFFD to produce the preliminary pedestrian detection results and a weak saliency map indicating the pedestrian regions. Then, the weak saliency map and the original thermal infrared image are combined to highlight the potential pedestrian regions and generate new results using the SF-LFFD. Finally, the pedestrian detection results obtained by the two improved networks are integrated to obtain the final results. The experimental results on the CVC-09 and CVC-14 datasets indicate that the proposed method significantly improves the average precision (AP) of pedestrian detection compared with that of existing lightweight neural networks, and that it achieves real-time detection with limited hardware resources.
Application of the Adaptive Wiener Filter in Infrared Image Denoising for Molten Steel
ZHAI Pan, WANG Ping
2021, 43(7): 665-669.
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The application of an infrared temperature measurement system reduces the occurrence of safety accidents during manual temperature measurement. However, the accuracy of the measurement depends on the quality of the image obtained using the infrared thermal imaging camera. To reduce the influence of noise on the quality of molten steel infrared images, this paper proposes a denoising method based on adaptive Wiener filtering. The autocorrelation parameter exponential decay model is used to control the computational complexity and sensitivity of the algorithm, thereby effectively improving the denoising performance of the Wiener filter. Based on the denoising processing of molten steel infrared images at different temperatures, it is verified that the proposed denoising method has better denoising performance than Wiener filtering and sparse decomposition methods.
Infrared Characteristics of Ground Targets and Background Observed from Near Space
YANG Jiajia, ZHOU Fangfang, CUI Lishan, ZHOU Ji
2021, 43(7): 670-678.
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Infrared radiation characteristics are the basis for target recognition in infrared detection systems. Based on the principle of radiation transmission, the infrared characteristics of the target and background in near space were studied. Using the global atmospheric profile to reflect the prior knowledge of the global atmospheric conditions, a set of radiation transmission simulation schemes were designed to study the infrared characteristics of ground targets detected from near space. The MODTRAN model was used for the simulations. The difference between the ground target and background detected in near space was quantified, and we analyzed the optimal transmission band of the sensor as well as the influencing factors of infrared radiation characteristics. The results show that the atmospheric transmittance and infrared radiation difference between the target and background decrease with an increase in the height of sensor and are closely related to the atmospheric conditions. The optimal transmission of the sensor in the range of 3-14μm was obtained; however, the influence of the season, atmospheric visibility, and sensor view zenith angle on the brightness temperature difference between the target and the background cannot be ignored.
Research on Component Identification for Electrical Equipment Based on Infrared Thermography
ZENG Jun, WANG Dongjie, FAN Wei, LIU Binbin, ZHAO Hongshan
2021, 43(7): 679-687.
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Common electrical equipment includes transformers, switchgears, and circuit breakers, which are composed of multiple components. In this study, the identification of these components was realized via infrared thermal imaging of such devices. Based on the characteristics of infrared thermal imaging with less information, a variety of algorithms have been used for fusion. First, based on the Lab model, a combination of improved K-means clustering and morphology was used to extract the high-temperature region in the infrared image, which guaranteed efficiency and reliability. Second, a combination of improved SURF and perceptual hash algorithms was used to determine the three-phase components in the extracted area. The role of SURF was to compare the visible image of the known electrical device with all the images in the extracted area to determine the area with the most matching feature points in the infrared image. Compared with other infrared regions, we found two regions with the highest matching degree in other regions via the perceptual hash algorithm to locate the three-phase devices in the infrared image. This study is applicable to infrared image recognition and positioning without a large number of image data sets and provides ideas for the extraction of fault information of electrical equipment based on infrared imaging.
Infrared Small Target Detection Method Based on Multi-Scale Feature Fusion
WANG Fang, LI Chuanqiang, WU Bo, YU Kun, JIN Chan, CHEN Yake, LU Yinghui
2021, 43(7): 688-695.
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Infrared small target detection is widely used in aerial target detection and tracking systems owing to its long detection range and strong anti-jamming ability. Aiming at to overcome the shortcomings of the current infrared small target detection algorithm, such as a low precision rate and high false alarm rate when dealing with complex backgrounds, we propose an end-to-end infrared small target detection model (called MFSSD) based on multi-scale feature fusion. Considering the traits of the targets, we propose a feature fusion module using a refinement and fusion feature map method and improve the correlation of different channels through the SP module. The experimental results of three different sequences of infrared image detection show that the average detection accuracy of the MFSSD algorithm for infrared small target detection was as high as 87.8%. Compared with those of the traditional multi-scale target detection algorithm, both the precision rate and recall rate have been significantly improved.
Underwater Image Restoration Method Combining Improved Red Channel Prior and Power Law Correction-based CLAHE Algorithm
ZHU Jiaqi, ZHOU Lili, YAN Jingjing, WANG Qiaoqiao, JIANG Yuhong, HE Lifeng
2021, 43(7): 696-701.
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An underwater image restoration method was proposed to address the issues of background light estimation deviation and contrast imbalance that occurs during the restoration of water degradation images. First, the background light area and value are determined according to the superpixel image segmentation method, and then the red channel prior theory is used to obtain the estimated transmittance and the preliminary restored image. Finally, the color of the restored image is enhanced using the normalized power law correction-based contrast limited adaptive histogram equalization (CLAHE) algorithm. Three image quality evaluation standards are used to objectively analyze the experimental results, and it is found that the proposed method can effectively balance the contrast and improve the visualization effect.
Pedestrian Perception Method Based on Infrared Stereo Vision
WANG Xiangjun, YANG Shouchang, CHEN Ruixiang
2021, 43(7): 702-708.
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Based on the thermal infrared characteristics, the infrared stereo vision pedestrian perception method can effectively detect and measure pedestrians in road scenes at night and hazy environments, with the aim of improving driving safety. Owing to less texture details in infrared images, the traditional dense binocular stereo matching algorithm performs poorly. To solve this problem, the region of interest (ROI) is extracted according to the brightness and edge features of the targets in the infrared image. Then, the image feature points are extracted and matched in the ROI to calculate the original sparse depth map. Finally, according to the small depth difference in the surface of the targets, the semi-dense depth map was estimated by combining the ROI and the original depth map. We designed an experimental system to verify the effectiveness of the proposed method. The experimental results showed that the relative error of the depth perception of pedestrians was better than 1.5% at 15 m and 3% at 30 m in the field of view of approximately 120°.
Ir Applications
Fruit Thermal Imaging Detection Based on Laplacian of Gaussian Algorithm
HAN Yahui, WANG Zhuo, LIU Jiaxin
2021, 43(7): 709-715.
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Traditional fruit grading and damage detection mostly use sensory evaluation methods. With the development of computer vision technology, automatic computer vision detection and grading technology developed rapidly. To solve the problem of fruit damage detection, we propose a technical scheme for fruit thermal imaging damage detection using image processing technology. In this scheme, the Laplacian of Gaussian (LoG) algorithm was used to detect the damaged parts; a Gaussian convolution template is used to suppress noise. Different convolution filter results were obtained by varying the convolution kernel sizes and σ values to enhance the color degree of the damaged part in the image. Then, the edge detection technology was used to obtain the edge information of the damaged part. In the experiment, apples with local damage were selected as the research object, and five evaluation methods, including references and non-references, were selected to analyze the influence of the convolution process on the edge detection of damaged parts. The experimental results show that the LoG algorithm can effectively detect the damaged parts of fruits during thermal imaging, and the influence of the convolution kernel size on the edge detection results is far greater than the value of σ. By increasing the size of the convolution kernel, the edge information of the damaged parts can be effectively deepened. This study provides a feasible solution for fruit damage area detection.

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