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Survey & Review
Review of Dim Small Target Detection Research in Single Infrared Image
FAN Zunlin, WANG Hao, GUAN Naiyang, YE Tingting, SUN Qianchong
2023, 45(11): 1133-1140.  
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For long-distance and wide field-of-view scenes, infrared target detection has significant challenges owing to the principle of a thermal imager, interference of the atmospheric environment, and attenuation of infrared radiation by long-distance transmission media. Based on the characteristic analysis of small-target infrared images, such as complex background, dim and small targets, low image contrast, and lack of image structures, we reviewed the research status of infrared dim small-target detection from target highlight and background estimation and discussed the development trend of infrared dim small-target detection.
Development of Highly Efficient Tandem White OLEDs
CHANG Cheng, QIAN Fuli, GOU Guoru, TANG Rui, WANG Tilu, GAO Sibo, ZHANG Weichenxi, HE Yangyang, LI Li, YANG Qiming, ZHANG Jie, LIU Yingqi, DUAN Yu, YANG Wenyun, WANG Guanghua
2023, 45(11): 1141-1152.  
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Tandem white OLEDs offer low power consumption, high brightness, and a high color gamut. However, the material and electrical structures of tandem white OLEDs still need to be optimized owing to the outstanding challenges in efficiency, lifetime, and driving voltage. In this study, we focused on the latest research on tandem white OLEDs and summarized the problems in engineering preparation and non-destructive detection method of 3 types of CGLs for high-efficiency tandem white OLEDs. We focused on the latest research on the "all-phosphorescent system, " "harvesting excitons via two parallel channels, " and the "mixed-phosphorescent-TADF system" simultaneously. We summarized the device lifetime problems and discussed structural solutions such as "graded doping" and "four-color mixed-phosphorescent-TADF system." From the aspect of CGL materials and structures in different systems, we reviewed the scheme of lower driving voltage for tandem white OLEDs. Finally, we provided suggestions for improving the materials and structures of tandem white OLEDs.
Image Processing and Simulation
Underwater Illumination Image Fusion Method Based on Color Correction
QIU Qimeng, ZHANG Yajia, GAO Zhiqiang, SHAO Jianlong
2023, 45(11): 1153-1160.  
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We proposed a color-corrected underwater illumination image fusion method based on color correction to address uneven color shifts, low contrast, and blurred details in underwater illumination images. First, we exploited the pixel correlation between image channels to compensate for the red channel. Then, based on the color-corrected image, a sharpness-enhanced image is obtained using a nonlinear unsharp masking technique, and a global stretching map is obtained using a restricted histogram with Rayleigh distribution. Finally, we generated the fused image using a multi-scale fusion strategy. The experimental results on a self-built dataset (RULI) showed that the proposed method could remove the inhomogeneous scattering interference of mixed illumination in the imaging process and substantially improve the detail sharpness of the image. The mean values of the image quality assessment metrics UIQM and IE were 4.7399 and 7.7617, respectively, better than those of related algorithms in the existing literature.
Infrared Blade Image Stitching Algorithm for Wind Farm UAV Inspection
ZHOU Dengke, GUO Xingchen, SHI Kaite, TANG Peng, ZHENG Kaiyuan, MA Pengge
2023, 45(11): 1161-1168.  
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Aiming at more redundant background information and low stitching accuracy of the infrared images of the blades taken by UAV (Unmanned Aerial Vehicle), In this study, we proposed a stitching algorithm for infrared wind turbine blade images combining the Chan-Vese model and morphology. First, we subjected the image to median filtering and noise reduction, and a morphological operation improved a level-set algorithm based on the Chan-Vese model to generate the mask of the expression subject. We extracted Harris feature points by removing redundant backgrounds based on the mask. We performed morphological etching on the mask to suppress the pseudo-feature points on the boundary-jagged pixels. We used violent matching and the RANSAC algorithm to screen out effective matching point pairs and calculate the homography matrix to realize matching and splicing. Compared with the Harris stitching algorithm under traditional image segmentation, the stitching accuracy of the improved algorithm significantly improved, and it showed strong robustness in different test scenarios.
Aerial Infrared Small Target Detection Algorithm Based on Structure Tensor Screening and Local Contrast Analysis
HE Bangsheng, WANG Zhonghua
2023, 45(11): 1169-1176.  
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Considering the false alarm and real-time requirements of infrared small-target detection under a complex cloud background, a novel algorithm is proposed based on structure tensor screening and local contrast analysis. Combined with the feature that the maximum eigenvalue of the structure tensor of the target area is larger than that of other background areas, the proposed algorithm can filter out most nontarget areas and retain a few suspicious areas. Local contrast calculation performed on suspicious areas can enhance the target, suppress the residual background, and effectively reduce computation. The algorithm steps are as follows: first, we constructed the structure tensor matrix within the local image area captured by the sliding window, and where the maximum eigenvalue is larger than the threshold is marked as a suspicious area. Then, we calculated the ratio-difference joint local contrast. Finally, we adopted an adaptive threshold segmentation on the saliency map to extract the real target. Experimental results showed that the proposed algorithm can achieve a higher detection rate, lower false alarm rate, and shorter running time under a complex cloud background.
Two-Stream Residual Dilation Network Algorithm for Crowd Counting Based on RGB-T Images
YANG Peilong, CHEN Shuyue, YANG Shangyu, WANG Jiahong
2023, 45(11): 1177-1186.  
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We proposed a multimodal crowd counting algorithm based on RGB-Thermal (RGB-T) images (two-stream residual expansion network) in crowd counting, given scale changes, uneven pedestrian distribution, and poor imaging conditions at night. It has a front-end feature extraction network, multi-scale residual dilation convolution, and global attention modules. We used the front-end network to extract RGB and thermal features, and the dilated convolution module further extracted pedestrian feature information at different scales and used the global attention module to establish dependencies between global features. We also introduced a new multi-scale dissimilarity loss method to improve the counting performance of the network and conducted comparative experiments on the RGBT crowd counting (RGBT-CC) and DroneRGBT datasets to evaluate the method. Experimental results showed that compared with the cross-modal collaborative representation learning (CMCRL) algorithm on the RGBT-CC dataset, the grid average mean absolute error (GAME (0)) and root mean squared error (RMSE) of this algorithm are reduced by 0.8 and 3.49, respectively. On the DroneRGBT dataset, the algorithm are reduced by 0.34 and 0.17, respectively, compared to the multimodal crowd counting network (MMCCN) algorithm, indicating better counting performance.
Remote Sensing Image Target Detection Method Based on CSE-YOLOv5
SHEN Lingyun, LANG Baihe, SONG Zhengxun, WEN Zhitao
2023, 45(11): 1187-1197.  
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We proposed a new object detection method based on the CSE-YOLOv5 (CBAM-SPPF-EIoU-YOLOv5) model for insufficient multi-scale feature learning ability and the difficulty of balancing detection accuracy and model parameter quantity in remote sensing image object detection algorithms in complex task scenarios. We built this method on the YOLOv5 model's backbone network framework and introduced a convolutional attention mechanism layer into the shallow layers to enhance the model's ability to extract refined features and suppress redundant information interference. In the deep layers, we constructed a spatial pyramid pooling fast (SPPF) with a tandem construction module and improved the statistical pooling method to fuse multi-scale key feature information from shallow to deep. In addition, we further enhanced the multi-scale feature learning ability by optimizing the anchor box mechanism and improving the loss function. The experimental results demonstrated the superior performance of the CSE-YOLOv5 series models on the publicly available datasets RSOD, DIOR, and DOTA. The average mean precisions (mAP@0.5) were 96.8%, 92.0%, and 71.0% for RSOD, DIOR, and DOTA, respectively. Furthermore, the average mAP@0.5:0.95 at a wider IoU range of 0.5 to 0.95 achieved 87.0%, 78.5%, and 61.9% on the same datasets. The inference speed of the model satisfied the real-time requirements. Compared to the YOLOv5 series models, the CSE-YOLOv5 model exhibited significant performance enhancements and surpassed other mainstream models in object detection.
Segmentation Method of Substation Equipment Infrared Image Based on Multimodal Image Information
ZHANG Zhichao, ZUO Leipeng, ZOU Jie, ZHAO Yaomin, SONG Yangfan
2023, 45(11): 1198-1206.  
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The segmentation accuracy of substation equipment in infrared images captured by a UAV directly affects the results of thermal fault diagnosis. We proposed a multimodal path aggregation network (MPAN) that fuses visible and infrared images to address the problem of low segmentation accuracy of substation equipment in complex infrared backgrounds. First, we extracted and fused the features of two modal images, and considering the differences in the feature space of the two modal images, we proposed the adaptive feature fuse module (AFFM) to fuse the two modal features fully. We added a bottom-up pyramid network to the backbone with multi-scale features and a laterally connected path enhancement. Finally, we used dice coefficients to optimize the mask loss function. The experimental results showed that the fusion of multimodal images can enhance the segmentation performance and verify the effectiveness of the proposed modules, which can significantly improve the accuracy of the segmentation of substation equipment instances in infrared images.
Multi-scale Auto-Corrected Bi-Histogram Equalization for Infrared Image Enhancement
ZHANG Huan, CHEN Zhisheng
2023, 45(11): 1207-1215.  
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We proposed a parameter self-tuning bi-histogram equalization method to solve saturation and detail loss in infrared image enhancement. We decomposed an input image into two independent sub-images according to the golden ratio of the gray cumulative probability density and modified each sub-image histogram through a multi-scale adaptive weighing process with input image exposure and sub-image gray-level interval information. Subsequently, we performed the equalization of the two corrected sub-histograms independently and combined the two equalized sub-images into a single output image. A test on 100 infrared images in a public dataset-INFRARED100 showed that, compared with brightness preserving bi-histogram equalization (BBHE), bi-histogram equalization with a plateau limit (BHEPL), and exposure-based sub-image histogram equalization (ESIHE), the images enhanced by the proposed method have appropriate contrast and greater average information entropy. We increased the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) index, and absolute mean brightness error (AMBE) by at least 17.2%, 4.0%, and 56.2% on average. The experiments illustrated that the proposed method is adaptable to infrared images with different brightness characteristics, effectively improving the contrast between the infrared image object and background. This method is superior to noise suppression, brightness, and detail preservation methods.
Two-scale Image Fusion of Visible and Infrared Images Based on Guided Filtering Decomposition
ZHANG Hui, HAN Xinning, HAN Huili, CHANG Lihong
2023, 45(11): 1216-1222.  
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We proposed a two-scale image-fusion method for infrared and visible light image fusion based on guided filtering to reduce the complexity of multi-scale decomposition fusion algorithms and improve the adaptability of fused images to human visual characteristics. First, we used guided filtering to enhance the visible image and decomposed the source images into base and detail layers using guided filtering. In the fusion rules of the detail layer, we adopted the energy protection methods and detail extraction. Finally, we combined the fused detail layer with the base layer to synthesize the fusion results. The experimental results showed that the proposed method improves the visual effect, detail processing, and edge protection. We discussed the impact of visible image enhancement on fusion methods from experimental data. Enhancement can improve the fusion effect, but the fusion method is key in image fusion.
Infrared and Visible Image Fusion of Unmanned Agricultural Machinery Based on PIE and CGAN
WANG Hongjun, YANG Yiming, ZHAO Hui, YUE Youjun
2023, 45(11): 1223-1229.  
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In this study, we proposed an infrared and visible image fusion algorithm that combines PIE and CGAN to make unmanned agricultural machinery perceive environmental information promptly and avoid accidents during production in complex environments. First, we trained the CGAN using an infrared image and corresponding saliency regions. The infrared image is input into the trained network to obtain the saliency region mask. After morphological optimization, we performed image fusion based on the PIE. Finally, we enhanced the fusion results by contrast processing. This algorithm can realize fast image fusion and satisfy the requirements for real-time environmental perception of unmanned agricultural machines. In addition, the algorithm retains the details of visible images and highlights important information concerning humans and animals in infrared images. It performs well in standard deviation and information entropy.
System & Design
Analysis of Composite Axis Control and Flyback Compensation Technology Based on Fast Reflector in Common Optical Patch
FANG Xibo, QIAO Honglei
2023, 45(11): 1230-1235.  
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Telephoto common optical path imaging components are widely used in photoelectric reconnaissance pods, and the technical development of telephoto common optical path fast mirrors for composite axis image stabilization has become an inevitable trend. This study introduced the main components of telephoto common optical path imaging components. We realized the composite axis control and flyback compensation control strategy based on a fast mirror and analyzed and calculated its working timing and key parameters. We developed a fast mirror based on a telephoto common optical path imaging device, and simultaneously realized secondary image stabilization and flyback compensation within one frame of the image. We improved the reconnaissance range, image stabilization accuracy, and the search effect of medium- and high-altitude photoelectric reconnaissance pods.
Analysis of Calibration Method and Occasion of Ground-based Infrared Imaging Equipments with Different FOVs
ZOU Qianjin, ZHANG Hengwei, WANG Dong, LIU Xiaohu, TIAN Zhuangzhuang
2023, 45(11): 1236-1241.  
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We can use the infrared radiation characteristics of a target for target recognition. Data on infrared radiation characteristics obtained by out-field infrared imaging equipment is significant in evaluating early warning, reconnaissance, and stealth effects. It is difficult to obtain the response coefficients of out-field infrared imaging equipment. We introduced and compared radiometric calibration methods using a collimator and an extended-area blackbody. We conducted experiments using different calibration methods and then provided response coefficients of the out-field infrared imaging equipment. The long-distance radiometric calibration results showed different response coefficients at different distances. An infrared imaging system conducted calibration experiments with different working times and fusions. The radiometric out-of-focus calibration results showed that diffusion is not the main factor influencing calibration. Calibration experiments for different working times also showed that the response coefficients remained unchanged. The factors affecting the radiometric calibration of the out-field infrared imaging equipment are environmental radiation, path radiation, and path transmission. Short-distance radiometric calibration using an extended-area blackbody is necessary to obtain the response coefficients of the out-field infrared imaging equipment. If the radiometric calibration distance is less than 10 m, the error between the short- and long-distance radiometric calibrations is approximately 5%. This research helps out-field radiometric calibration of ground-based infrared imaging equipment and designs a radiometric calibration–measuring system.
Materials & Devices
Surface Processing of Cadmium Zinc Telluride Substrates
JIANG Xianyan, CONG Shuren, NING Zhuo, QI Wenbin, LIU Yan, SONG Linwei, KONG Jincheng
2023, 45(11): 1242-1255.  
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In this study, the surface processing of cadmium zinc telluride (CZT) substrates was studied, which revealed surface dislocation defects. The surface processing mechanism and influence of the process parameters on the surface of the CZT substrates, including mechanical grinding, mechanical polishing, chemical mechanical polishing, and chemical polishing, are presented. Moreover, three types of chemical etchants, Everson, Nakagawa, and EAg, which reveal dislocation defects on the surface of CdZnTe with different crystal orientations, were also investigated.
Nondestructive Testing
Infrared Image Fault Detection Method of Arrester Based on Improved YOLOv3
HU Taishan, LIU Hao, LIU Gang, MEI Qi, MA Yutang, LIAO Minchuan
2023, 45(11): 1256-1261.  
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Aiming at the problems of low recognition accuracy and slow detection speed of existing metal oxide arrester (MOA) infrared image fault detection methods, a MOA infrared image fault detection method based on improved YOLOv3 is proposed. Firstly, darknet19 network is used to replace the original darknet53 network of YOLOv3. During feature learning, the target frames in MOA images are analyzed by K-means clustering algorithm according to different MOA length width ratios in samples. The anchor frames in the center of samples are re clustered to get the appropriate number and size of anchor frames. Finally, the improved YOLOv3 model is used to complete the MOA infrared image fault detection. The experimental results show that the recognition accuracy of the improved model reaches 96.3%, and the recognition speed is 6.75ms.
Present State and Perspectives of Small Infrared Targets Detection Technology
HOU Wang, SUN Xiao-liang, SHANG Yang, YU Qi-feng
2015, 37(1): 1-10.  
[Abstract](661) [PDF 2162KB](126)
Research Development of Infrared Stealth Materials
SHEN Yulian, LI Chunhai, GUO Shaoyun, CHEN Rong
2021, 43(4): 312-323.  
[Abstract](975) [FullText HTML](421) [PDF 1128KB](348)
Uncooled Infrared FPA--A Review and Forecast
FENG Tao, JIN Wei-qi, SI Jun-jie
2015, (3): 177-184.  
[Abstract](959) [PDF 1085KB](91)
Infrared Thermography NDT and Its Development
2018, 40(5): 401-411.  
[Abstract](298) [PDF 1575KB](40)
Research on Influence Factors for Measuring and Method of Correction in Infrared Thermometer
LIAO Panpan, ZHANG Jiamin
2017, 39(2): 173-177.  
[Abstract](342) [PDF 1228KB](56)
Research Review of 3D Cameras Based on Time-of-Flight Method
WEI Jiali, QU Huidong, WANG Yongxian, ZHU Junqing, GUAN Yingjun
2021, 43(1): 60-67.  
[Abstract](603) [FullText HTML](155) [PDF 549KB](141)
Infrared Image Detail Enhancement Algorithm Based on Hierarchical Processing by Guided Image Filter
GE Peng, YANG Bo, HAN Qinglin, LIU Peng, CHEN Shugang, HU Douming, ZHANG Qiaoyan
2018, 40(12): 1161-1169.  
[Abstract](243) [PDF 2514KB](37)
Developments of High Performance Short-wave Infrared InGaAs Focal Plane Detectors
SHAO Xiumei, GONG Haimei, LI Xue, FANG Jiaxiong, TANG Hengjing, LI Tao, HUANG Songlei, HUANG Zhangchen
2016, 38(8): 629-635.  
[Abstract](433) [PDF 900KB](48)
中科院上海技物所近十年来开展了高性能短波红外 InGaAs 焦平面探测器的研究。0.9~1.7?m近红外 InGaAs 焦平面探测器已实现了256×1、512×1、1024×1等多种线列规格,以及320×256、640×512、4000×128等面阵,室温暗电流密度<5 nA/cm2,室温峰值探测率优于5×1012 cm?Hz1/2/W。同时,开展了向可见波段拓展的320×256焦平面探测器研究,光谱范围0.5~1.7?m,在0.8?m 的量子效率约20%,在1.0?m 的量子效率约45%。针对高光谱应用需求,上海技物所开展了1.0~2.5?m 短波红外 InGaAs 探测器研究,暗电流密度小于10 nA/cm2@200 K,形成了512×256、1024×128等多规格探测器,峰值量子效率高于75%,峰值探测率优于5×1011 cm?Hz1/2/W。
Read Out Integrated Circuit for Third-Generation Infrared Focal Plane Detector
BAI Pi-ji, YAO Li-bin
2015, (2): 89-96.  
[Abstract](813) [PDF 738KB](87)
对红外探测器不断增长和提高的需求催生了第三代红外焦平面探测器技术。根据第三代红外探测器的概念,像素达到百万级,热灵敏度NETD达到1 mK量级是第三代制冷型高性能红外焦平面探测器的基本特征。计算结果表明读出电路需要达到1000 Me-以上的电荷处理能力和100 dB左右的动态范围(Dynamic Range)才能满足上述第三代红外焦平面探测器需求。提出在像素内进行数字积分技术,以期突破传统模拟读出电路的电荷存储量和动态范围瓶颈限制,使高空间分辨率、高温度分辨率及高帧频的第三代高性能制冷型红外焦平面探测器得到实现。
Infrared Image Denoising Method Based on Improved Non-local Means Filter
GUO Chenlong, ZHAO Xuyang, ZHENG Haiyan, LIANG Xining
2018, 40(7): 638-641.  
[Abstract](119) [PDF 982KB](16)
提出了一种基于梯度信息的结构相似性算法改进的红外图像非局部均值滤波方法.传统的非局部均值滤波算法采用欧氏距离度量图像块之间的相似性,因而不能够很好地衡量图像细节和边缘信息,导致滤波后图像模糊失真.针对此问题,采用结构相似性度量(structural similarity,SSIM)算法对欧氏距离进行加权改进,针对普通的SSIM边缘信息评价能力的不足,提出了带有梯度信息的GSSIM算法,实验结果表明本方法在保持非局部均值(Non-Local Means,NLM)滤波算法去噪能力的同时还能够较好地保持图像的边缘和细节信息.
Research Progress and Application of Polarization Imaging Technology
ZHOU Qiangguo, HUANG Zhiming, ZHOU Wei
2021, 43(9): 817-828.  
[Abstract](1338) [FullText HTML](1556) [PDF 1293KB](1556)
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.
Research Development of Infrared Stealth Materials
SHEN Yulian, LI Chunhai, GUO Shaoyun, CHEN Rong
2021, 43(4): 312-323.  
[Abstract](975) [FullText HTML](421) [PDF 1128KB](421)
With the rapid development of infrared detection technology, the improvement of the infrared stealth capability of military targets has become an urgent problem to be solved, so it is of great significance to study infrared stealth materials. This paper briefly analyzes the stealth mechanism of infrared stealth materials, summarizes the research status of four types of infrared stealth materials in recent years, such as low infrared emissivity materials, temperature control materials, photonic crystals, and intelligent infrared stealth materials, and forecasts the future development trend of infrared stealth materials.

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Monthly, Established 1979

Competent Authorities:China North Industries Group Corporation

Sponsored by:Kunming Institute of Physics
China Ordnance Society, Speciality



Postal distribution code:64-26

Editorial Office:No.31 Jiao Chang Dong Road, Kunming, 650223, China


Infrared technology is one of the earliest photoelectronic journals in China.Infrared Technology is published by Science Press, and it is a single monthly technical journal.

Infrared Technology is a professional and academic journal based on scientific research, which comprehensively reflects the research progress of infrared technology at home and abroad and its application in national defense, industry, agriculture and national economy.After years of efforts, INFRARED Technology has become the core journal of Chinese, The core journal of Chinese science and technology, and the source journal of Chinese Science citation database.

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