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2021 Vol. 43, No. 9

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Survey & Review
High Performance Super Second Generation Image Intensifier and Its Further Development
LI Xiaofeng, ZHAO Heng, ZHANG Yanyun, ZHANG Qindong
2021, 43(9): 811-816.
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Abstract:
This paper presents the technical characteristics and performance of high performance super second generation image intensifier, compares it with ordinary super second generation image intensifier, and puts forward the technical measures to further improve the performance of high performance super second generation image intensifier. Super second generation image intensifier is a kind of image intensifier with higher performance over second generation image intensifier. It was developed by application of new technology, new craft and new material on the base of the second generation image intensifier. After nearly 30 years of development, its performance has been greatly improved. In recent years, due to the use of grating window on the super second generation image intensifier, the sensitivity of the Na2KSb photocathode is over 1000 μA·lm-1, and the resolution is above 17 lp·mm-1 on the illumination of 10-4 lx. It would be predicted that the sensitivity of Na2KSb photocathode will reach 1350-1800 μA·lm-1, and the signal-to-noise ratio will reach 35-40 by further improving the fabrication process of Na2KSb film and optimizing the structure of grating. It would be predicted that the resolution will reach 81 lp·mm-1through use of microchannel plate of 4 (m diameter and fiber optical plate of 3 μm diameter, the resolution is likely to reach 81 lp·mm-1.
Research Progress and Application of Polarization Imaging Technology
ZHOU Qiangguo, HUANG Zhiming, ZHOU Wei
2021, 43(9): 817-828.
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The advantage of polarization imaging technology is that it expands the amount of information from three degrees of freedom, namely light intensity, spectrum, and space, to seven degrees of freedom, including light intensity, spectrum, space, degree of polarization, polarization azimuth, polarization ellipticity, and direction of rotation. This richness of observational information is conducive to improving the accuracy of research target detection. This article first introduces the research progress of polarization imaging technology at home and abroad in recent decades, then introduces the typical applications of polarization technology in military and civilian fields, and finally provides reasonable suggestions on the problems of polarization imaging technology in our country.
Systems & Designs
Study on Machining Technology of Large Aspheric Aluminum Reflector with Three Axis Linkage
XIAO Jiaoguo, YAO Tong, ZHANG Wanqing, LIU Yao, LUO Hong, LI Maozhong, HUANG Pan, KANG Jie, ZHANG Ruoyin
2021, 43(9): 829-835.
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Abstract:
To solve the problem of single point diamond turning(SPDT), technology was used for the processing of large diameter and chord height aspheric aluminum mirrors, which have the problems of limited lathe guide stroke, limited rotary volume of worktable, and low processing quality. To process a concave aspheric aluminum mirror with a diameter of φ682 mm and a chord height of 220 mm, first, a three-axis linkage processing method based on SPDT was proposed, which adds rotary b-axis on the basis of two-axis processing, such that the guide rail travel and table rotation volume can meet the processing requirements. Then, the special cage fixture was designed, and the influence of the number of supporting rods, the diameter of supporting rods, and the thickness of upper and lower connecting plates on the jig-work piece deformation characteristics were examined using the finite element method. The influence of different factors on the maximum deformation of jig and work piece was evaluated via range and variance analysis. A set of optimal jig design parameters was obtained, that is, the number of jig support rods was 24, the diameter of the rods was 22 mm, and the thickness of the upper and lower connecting plates was 25 mm. Finally, the aluminum mirror was fixed on the optimized cage clamp, and the processing of the φ682 mm aspheric aluminum mirror was realized through three-axis linkage processing. The test results show that the surface accuracy Pv of the tool adjusting part was 0.6 μm, and the surface roughness Ra was approximately 10.1 nm. It can be considered that the surface accuracy and surface roughness of the φ682 mm aspheric aluminum mirror can meet the requirements. This study can provide a theoretical basis and technological reference for the processing of the same type of large aperture and high chord aspheric mirror.
LWIR Optical System Design by Passive Athermalization
ZHOU Xiaobin, ZHANG Heng, WEN Jianghua, WU Yan, LIU Zhaoqing, ZHANG Xiangming, JIN Mingxin
2021, 43(9): 836-839.
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A low-cost and high-quality hybrid passive athermalization method for LWIR was proposed by combining passive optical and passive mechanical athermalization. An athermalization optical system with a focal length of 75 mm and F/1 was designed using passive optical and hybrid passive athermalization. Compared with traditional passive mechanical athermalization, the volume and complexity of the thermal compensation structure can be reduced using hybrid passive athermalization. In addition, the proposed method decreases the volume and weight of the system. Compared with passive optical athermalization, hybrid passive athermalization can reduce the volume and processing difficulty when the imaging quality is the same. Thus, the propose method can be used to achieve a low-cost, high-quality, long-wave athermalization system.
Image Processing and Simulation
Asymmetric Infrared and Visible Image Fusion Based on Contrast Pyramid and Bilateral Filtering
YANG Jiuzhang, LIU Weijian, CHENG Yang
2021, 43(9): 840-844.
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This study proposes an asymmetric infrared and visible image fusion method based on a contrast pyramid to save the feature information of infrared image and the detail information of visible image simultaneously. First, the contrast pyramid is used to decompose the high-frequency and low-frequency information of the infrared and visible images; then, the high-frequency part is fused by taking the largest absolute value, and the low-frequency part is processed differently by the method based on bilateral filtering. Second, the inverse transform of the contrast pyramid was used to obtain the fused image. Subjective visual and objective index evaluations were conducted on the fused image. The results show that the algorithm performs well in highlighting the target feature information and retaining detailed feature information.
Silent Live Face Detection in Near-Infrared Images Based on Optimized LeNet-5
HUANG Jun, ZHANG Nana, ZHANG Hui
2021, 43(9): 845-851.
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An improved method of silent liveness detection for LeNet-5 and near-infrared images is proposed to overcome the problem of the interactive liveness detection process and poor user experience. First, a face attack dataset was constructed using a near-infrared camera. Second, the LeNet-5 was optimized by increasing the number of convolution kernels and introducing global average pooling to construct a deep convolutional neural network. Finally, the near-infrared face image is input to the model to realize silent liveness detection. The experimental results show that the proposed model has a higher recognition rate for the liveness detection dataset, reaching 99.95%. The running speed of the silent liveness detection system is approximately 18-22 frames per second, which shows high robustness in practical applications.
Infrared Pedestrian Action Recognition Based on Improved Spatial-temporal Two-stream Convolution Network
JIANG Yi, HOU Liping, ZHANG Qiang
2021, 43(9): 852-860.
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This study proposes an improved spatial-temporal two-stream network to improve the pedestrian action recognition accuracy of infrared sequences in complex backgrounds. First, a deep differential network replaces the temporal stream network to improve the representation ability and extraction efficiency of spatio-temporal features. Then, the improved softmax loss function based on the decision-making level feature fusion mechanism is used to train the model, which can retain the spatio-temporal characteristics of images between different network frames to a greater extent and reflect the action category of pedestrians more realistically. Simulation results show that the proposed improved network achieves 87% recognition accuracy on the self-built infrared dataset, and the computational efficiency is improved by 25%, which has a high engineering application value.
Image Fusion Algorithm Based on Thermal Radiation Information Retention
QIAN Zhenlong, CHEN Bo
2021, 43(9): 861-868.
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Focusing on the issue that existing algorithms of infrared and visible image fusion cannot retain thermal radiation information from infrared images, an image fusion algorithm based on thermal radiation information retention was proposed. Multi-scale decomposition of infrared and visible light images was performed through NSCT transformation to obtain the respective high-frequency sub-bands and low-frequency sub-bands. The low-frequency sub-bands of visible light were extracted by the Laplacian and superimposed with the infrared low-frequency sub-bands to obtain low-frequency sub-bands of the fused image. The fusion rule, which is based on point sharpness, and detail enhancement were used to obtain the high-frequency coefficients of the high-frequency part; the fused image was then reconstructed through inverse NSCT transformation. The experimental results indicate that compared with other image fusion algorithms, the proposed algorithm can retain the thermal radiation information of infrared images, while maintaining good performance with clear details, and is superior to other algorithms in several objective evaluation indices. The proposed algorithm has better visual effects and a good visual experience after pseudo-color transformation, which verifies the effectiveness and feasibility of the proposed algorithm.
Real-time Dynamic Blind Pixel Detection and Compensation Method for Mid-wave Infrared Camera
SUN Chao, ZHANG Hongwen, WANG Pei, LI Jun
2021, 43(9): 869-875.
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The existence of blind pixels significantly affects the imaging quality of infrared cameras. Scene-based methods for blind pixel detection and compensation can effectively solve such problems. This study proposes an improved local "3σ" method. The average noise of the infrared image is obtained by calculating the three-dimensional noise of the image; according to this average noise, the minimum criterion for blind pixel detection is obtained. Subsequently, real-time dynamic detection and compensation for blind pixel is performed by local "3σ" and median filtering method; furthermore, the method was applied to a self-developed mid-wave infrared camera. The results of the blackbody imaging experiment show that, compared with the radiation calibration method, the coincidence degree of blind pixel detection of our method can exceed 82% on average. The proposed method has the same effect of detection and compensation for blind pixel compared with the traditional local "3σ" method; however, it can reduce the over-detection rate of blind pixel by more than 30%.The results of imaging experiments of ground scene show that the proposed method can effectively restrain the blind pixel, and no apparent abnormal black and white spots were found in both daytime and nighttime images captured by the infrared camera. Additionally, the scene details in the images are rich, and the image quality is excellent. Therefore, the method presented in this study has good performance in real-time dynamic blind pixel detection and compensation. It is feasible and effective for use in self-developed mid-wave infrared cameras.
Improved Infrared Image Edge Detection Algorithm Based on DexiNed
HE Qian, LIU Boyun
2021, 43(9): 876-884.
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Abstract:
Compared with optical image edge detection, there are fewer studies on infrared image edge detection, and most of them are based on traditional methods, such as edge detection operators and mathematical morphology. In essence, they only consider the sharp local changes of infrared images to detect edges, so they are always limited by low-level features. In this paper, an infrared image edge detection algorithm based on deep learning is proposed. Based on the dense extreme inception network for edge detection (DexiNed), the network capacity is reduced by removing the last main block, the image level difference is introduced into the loss function, and the parameters of the loss function are carefully set to optimize the network performance. In addition, by adjusting the natural image edge detection dataset to approximate the infrared image edge detection dataset, the improved model was trained to enhance the edge detection ability. The qualitative evaluation results show that the edge of the infrared image extracted by our method is accurate, precise, rich in detail, and fits human vision. A quantitative evaluation using the structural similarity indexmatrix (SSIM) and feature similarity indexmatrix (FSIM) indexes further shows the advantages of our method compared with other existing methods.
Improved Infrared Anomaly Target Detection Algorithm Based on Single Gaussian Model
SONG Shanshan, ZHAI Xuping
2021, 43(9): 885-888,894.
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Abstract:
An infrared anomaly target detection algorithm based on a single Gaussian model is a commonly used detection algorithm that can adaptively update the background model. The algorithm performs Gaussian modeling on the output response of each pixel and determines whether the target pixel is a foreground pixel through a defined threshold to realize detection. This paper proposes an improved anomaly detection algorithm based on a single Gaussian model. The algorithm uses the Neiman-Pearson criterion to define the optimal threshold, which overcomes the limitation of selecting the threshold based on empirical values. The paper lays a theoretical foundation for obtaining the best decision threshold so that under a certain false rate, the detection probability can reach the highest value. Experimental results show that, compared to the commonly experienced thresholds, the threshold determined in this study provides a much better detection effect.
Low-Light-Level
Fault Diagnosis of Reliability Test for Low-Light-Level Vision Device Based on Structural Similarity Algorithm
LI Yongtao, HE Yalei, WU Fengling
2021, 43(9): 889-894.
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At present, fault diagnosis in direct-view low-light-level photo-optical equipment is mainly conducted by manual detection, which is inefficient, error prone (faults will often be missed), and does not create a valid record. This paper proposes an automatic diagnostic method based on machine vision. In this method, a series of special adaptors are designed for developing a reliable connection between the industrial camera and the object to be tested, automatically collecting the images of the eyepiece field of view image of the tested product, and transmitting the monitoring image in real time. We used the Structural SIMilarity (SSIM) algorithm to calculate the similarity between the monitoring images and the template image in real time to automatically warn of abnormalities using a judgment threshold, which is determined in advance. When a failure occurs, the system issues an abnormal warning, generates a detection log, and stores the current monitoring images. Practice shows consistency of the results of our method with those of subjective judgment. Under stable illumination conditions, the accuracy of the diagnostic technique meets the actual requirements.
Measurements
Accuracy Compensation Method for Infrared Human Body Temperature Measurement Accuracy
LU Zhifei, LIU Haoyu, CHEN Wenliang, WANG Xiangjun
2021, 43(9): 895-901.
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To address the problems of low measurement accuracy and limited use conditions of existing human body temperature measurement schemes, a non-contact human body temperature measurement accuracy compensation method based on infrared thermal imaging is studied. Considering the influence of temperature measurement devices and environments on the measurement accuracies, we need to solve the problems of infrared camera output values drifting with time, periodic signal chopping of an infrared camera, constant change in temperature measurement distance, and frequency domain noise of the temperature output value. To solve these problems, a comprehensive temperature measurement accuracy compensation method is proposed to effectively reduce the temperature measurement error. The experiment showed that the errors in human body temperature measurement under different distances were less than 0.2℃ using the precision compensation method in this study, which can realize accurate human body temperature measurement.
Materials & Devices
Small Pixel 10 μm Pitch Infrared Focal Plane Array ROIC Design
WU Shengjuan, YAO Libin, LI Dongsheng, JI Yulong, YANG Chunli, LI Hongfu, LUO Min, LI Min, XU Ruihan
2021, 43(9): 902-909.
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Abstract:
A kind of infrared focal plane CMOS (complementary metal oxide semiconductor) read out integrated circuit (ROIC) for small pixel applications was developed. This ROIC design includes ITR(integration then reading) and IWR(integration while reading)functions, two gains in ITR mode, charge capacities are 4.3 Me- and 1.6 Me-. Other functions include anti-blooming, series port control function and full chip current injection test function. This ROIC was fabricated in 0.18μm process, power supply voltage 3.3 V, test result show good performance of the ROIC, full frame rate is 100 Hz, noise of readout circuit is 0.2 mV. This paper introduces the basic structure of the readout circuit design, and analyzes the design of anti-interference ability of the circuit under the condition of small integral capacitance; During the test, tailing phenomenon is found, the causes of the tailing phenomenon is analyzed and In order to solve the tailing phenomenon, the Anti-blooming voltage generation circuit is designed, and the test results of the whole circuit are given at the end of the paper.
Nondestructive
Thermal Fault Diagnosis of Power Equipments Based on Guided Filter
HUANG Zhihong, WU Sheng, XIAO Jian, ZHANG Keren, HUANG Wei
2021, 43(9): 910-915.
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Thermal fault is a common fault type in the power equipment. This paper introduces a thermal fault diagnosis method for the power equipment by employing guided filter. The proposed method consists of two main steps. First, according to the temperature difference between the thermal fault area and the background in infrared images, the Mahalanobis distance between the fault area and the background is estimated, and the initial thermal fault diagnosis results can be generated. Then, guided filter is used to improve the diagnosis performance, by utilizing the spatial correlation between adjacent pixels fully utilized. Experimental results demonstrate that the proposed diagnosis method has a better diagnosis performance than the current state-of-the-art detectors.

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