Contents
2025
Volume: 47 Issue 4
18 Article(s)
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Stray Light Suppression of Coaxial Optical System for Space-Based Infrared Detection of Space Target
Fanduo MENG, Xiao WANG, Weiming TONG, Xinghua GAO, and Wenpo MA
Space-based infrared detection systems for space targets are affected by strong stray light from the Earth and atmosphere outside the field of view when detecting faint targets in low Earth orbit. Therefore, such detection systems have high requirements for stray light suppression. Based on the requirements of space-baSpace-based infrared detection systems for space targets are affected by strong stray light from the Earth and atmosphere outside the field of view when detecting faint targets in low Earth orbit. Therefore, such detection systems have high requirements for stray light suppression. Based on the requirements of space-based infrared detection for space targets, this study analyzes the stray light suppression technologies of several foreign space-based infrared detection systems, investigates the stray light suppression technology of coaxial optical systems used for space-based infrared detection of space targets, and proposes a technical approach to further improve stray light suppression by adding a center baffle to the back of the secondary mirror. Using SABER's coaxial optical system as an example, the stray light suppression capability was simulated before and after adding the center baffle. The simulation results show that, after adding the center baffle to the back of the secondary mirror, the point source transmittance (PST) of the optical system in the detection direction at the edge is significantly reduced by 46% and 35% when the off-axis angles are 5° and 10°, respectively..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 403 (2025)
Simplified Calculation Method of FY-3D Satellite MERSI-II Thermal Infrared Channel Split-Window Simulation
Wenfei WU, Zhengqiang LI, Qian YAO, Shikai ZHOU, Hua XU, Zhenting CHEN, and Qifeng JIANG
The split-window algorithm has been widely applied for surface temperature inversion of various satellite payloads. The iterative simulation of large datasets during the fitting of split-window algorithm coefficients is often time-consuming and inefficient. Therefore, it is important to develop a highly efficient simplThe split-window algorithm has been widely applied for surface temperature inversion of various satellite payloads. The iterative simulation of large datasets during the fitting of split-window algorithm coefficients is often time-consuming and inefficient. Therefore, it is important to develop a highly efficient simplification method for split-window simulation computations. MODTRAN was to simulate and analyze the impact of variations in background parameters on total radiance. Subsequently, we performed a simulation analysis of the relationship between key parameters and total radiance under two adjacent thermal infrared channels of FY-3D MERSI-II, exploring the variation patterns of total radiance under different coupling scenarios of these key parameters. Simulation results reveal that under the MERSI-II thermal infrared channels, changes in land surface temperature have a greater impact on total radiance than surface emissivity. The effect of the atmospheric water vapor content concentration on the total radiance increases with an increase in both the land surface emissivity and land surface temperature, whereas the influence of the land surface emissivity and land surface temperature on the total radiance decreases as the atmospheric water vapor content concentration increases. When determining the coefficients for the split-window algorithm, narrowing the range of the atmospheric water vapor content concentration can reduce the number of simulations required, thereby enhancing the efficiency. For land surface temperatures ranging from 300 to 320 K, the atmospheric water vapor content concentration should be within 0.5 to 5.5 g/cm2; for temperatures ranging from 270 to 300 K, this range narrows to 0.5 to 4.0 g/cm2. The saved simulation runs account for 18.23% of the total number of runs, which reduces the simulation time by 26 min. A comparison of the split-window coefficient fitting and absolute difference calculation results before and after simplification shows that the simplified scheme has minimal impact on the fitting outcomes..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 410 (2025)
Influence of Auto-Gated Power Supply on the Performance of Image Intensifier
Yaqing LI, Zhuang YANG, Tianli GAO, Shengtao ZHOU, Xiaolu LI, Yuanxi BAO, Peide DU, Jinghao DAI, Jun HE, Liyun ZHANG, Qigeng SONG, Guangfan WANG, Lingji XU, and Xu ZHANG
To explore the relationship between the cathode pulse and signal-to-noise ratio (SNR), MCP voltage, imaging clarity, voltage between the MCP and anode, brightness stability, and the dynamic range of an image intensifier using different auto-gated power supplies, experiments were conducted using the same image intensifiTo explore the relationship between the cathode pulse and signal-to-noise ratio (SNR), MCP voltage, imaging clarity, voltage between the MCP and anode, brightness stability, and the dynamic range of an image intensifier using different auto-gated power supplies, experiments were conducted using the same image intensifier tube with two types of auto-gated power supplies. The results show that the DC voltage of the cathode under low illumination can effectively improve the SNR of the image intensifier. Reducing the intermediate value of the MCP voltage can enhance the limited resolution and MTF of the image intensifier to a certain extent. A constant voltage between the MCP and anode can significantly improve the brightness stability of the image intensifier, and the maximum random fluctuation, steady-state drift, and maximum steady-state deviation under saturated illumination are substantially improved. The maximum working illuminance of the image intensifier with both types of auto-gated power supplies exceeds 1×104 lx, and the new auto-gated power supply can further expand the dynamic range of the image intensifier..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 421 (2025)
Hyperspectral Image Classification Based on Improved Semantic AutoEncoder Network in Unbalanced Small-Sized Labeled Samples
Baogang SUN, and Guobin HE
To improve the classification performance of hyperspectral images with unbalanced, few-labeled samples, an improved semantic autoencoder network is proposed in this paper. This network first introduces hyperspectral category-label information into the semantic autoencoder model, establishing the association between knoTo improve the classification performance of hyperspectral images with unbalanced, few-labeled samples, an improved semantic autoencoder network is proposed in this paper. This network first introduces hyperspectral category-label information into the semantic autoencoder model, establishing the association between known and unknown categories by mapping the original data and label information of different datasets to the same feature space. It then maps the training dataset features to the unified embedding space to learn the correspondence between the visual features and the semantic features of the category labels. Finally, an objective function based on a graph regularization term is constructed to preserve the feature manifold structure in the dataset, and the global problem is decomposed into several smaller, more manageable local subproblems using the alternating direction multiplier method to obtain the global optimal solution. Three hyperspectral datasets with different spectral dimensions, numbers of spectral bands, and land cover types were selected to ensure the diversity of the experimental data. The results showed that the proposed method achieved better classification accuracy with a small number of labeled samples compared with other state-of-the-art methods, making it suitable for the engineering classification of unbalanced hyperspectral image data..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 429 (2025)
Infrared Object Tracking Algorithm Based on Two-stage Spatiotemporal Weighted Features
Qingzhong LI
This paper proposes an infrared object tracking algorithm based on two-stage spatiotemporally weighted features. First, the object area is divided into non-overlapping areas of the same size, and different weights are assigned to different location information, from which an adaptive spatiotemporal weighted Bayesian clThis paper proposes an infrared object tracking algorithm based on two-stage spatiotemporally weighted features. First, the object area is divided into non-overlapping areas of the same size, and different weights are assigned to different location information, from which an adaptive spatiotemporal weighted Bayesian classifier is derived. An improved metric is then used to identify classification samples with the maximum class difference, which have high tracking adaptability, and to enable re-capture and tracking when the target is occluded. Simulation experiments show that, compared with mainstream tracking algorithms such as SiamFC, the proposed algorithm achieves significant improvements in overlap rate and central error indicators on the LSOTB-TIR target tracking dataset, significantly enhancing tracking stability and positioning accuracy. The tracking speed reaches 56 F/s, making it suitable for engineering applications..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 437 (2025)
Electronic Zooming of Infrared Image Based on Lightweight Multi-scale Aggregation Network
Xin LIU, and Bin ZHANG
To solve the problem of low-resolution infrared images affecting viewing and aiming in the photoelectric field, a lightweight multi-scale aggregation network is proposed to enhance the resolution of the central region when the IR image is zoomed. First, the algorithm uses scale kernels of different sizes to extract feaTo solve the problem of low-resolution infrared images affecting viewing and aiming in the photoelectric field, a lightweight multi-scale aggregation network is proposed to enhance the resolution of the central region when the IR image is zoomed. First, the algorithm uses scale kernels of different sizes to extract feature information and employs a shallow residual structure to effectively aggregate local multi-scale residual features, thereby obtaining stronger feature representation capability. Then, a channel attention layer based on contrast perception is used to aggregate more multi-scale feature information. Finally, a high-resolution infrared image with rich detail and clarity is reconstructed. Simulation results show that the zooming method can extract fine multi-scale feature information without introducing additional parameters and can produce clear reconstruction results..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 445 (2025)
A Deep Learning Method for Hyperspectral Detection of Heavy Metal Contaminants in Soil Based on Attention Mechanism
Ye YE
Hyperspectral imaging and deep learning techniques provide new methods and tools for detecting soil contaminants. This study explores a convolutional neural network (CNN)-based algorithm for the detection of hyperspectral soil contaminants. First, a hyperspectral soil dataset containing multiple spectral bands was collHyperspectral imaging and deep learning techniques provide new methods and tools for detecting soil contaminants. This study explores a convolutional neural network (CNN)-based algorithm for the detection of hyperspectral soil contaminants. First, a hyperspectral soil dataset containing multiple spectral bands was collected, and data analysis and feature extraction were performed. Subsequently, a CNN architecture adapted to the characteristics of hyperspectral soil data was designed. A self-attention mechanism was introduced to automatically reduce the dimensionality of redundant spectral data, and a feature fusion structure using graph features was employed for feature extraction. Finally, the performance of the algorithm was validated using a collected soil contaminant dataset. The experimental results demonstrate that the proposed method effectively reduces the dimensionality of hyperspectral data, decreases data redundancy, and achieves good performance and accuracy in soil contaminant detection by incorporating graph features. This method is of practical significance for the rapid detection of soil contaminants..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 453 (2025)
Infrared Multi-Scale Target Detection Algorithm Based on RCR-YOLO
Xiaohan CHEN, and Yuanyuan XU
Infrared target detection has been widely used in both military and civilian fields. To address the issues of missed and false detections in infrared multi-scale target detection under complex backgrounds, an improved YOLOv5s algorithm, RCR-YOLO, is proposed in this paper. First, the backbone network CSPDarkNet53 of thInfrared target detection has been widely used in both military and civilian fields. To address the issues of missed and false detections in infrared multi-scale target detection under complex backgrounds, an improved YOLOv5s algorithm, RCR-YOLO, is proposed in this paper. First, the backbone network CSPDarkNet53 of the original YOLOv5s was replaced with ResNet50 to avoid gradient vanishing caused by the deep network and to enhance the network's feature extraction capability. Subsequently, the CA attention mechanism module was added to the end of the backbone to capture feature information from different locations. Finally, the Res2Net module was added to the neck network to improve the network's representational ability and process multi-scale feature information by introducing a multi-branch structure and progressively increasing resolution, thereby enhancing detection performance. Experimental results show that this method outperforms mainstream target detection algorithms such as Faster R-CNN, SSD, and YOLOv3. Compared to YOLOv5s, mAP50–95 increased by 1.1%, while mAP50 remained at 99.5%, indicating better detection performance. The algorithm effectively performs multi-scale infrared target detection under complex backgrounds..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 459 (2025)
Multimodal Object Detection Based on Feature Interaction and Adaptive Grouping Fusion
Zhihui YE, Jian WU, Xiaozhong ZHAO, Wenjuan WANG, and Xinguang SHAO
To improve the performance of object detection methods in complex scenes, a multimodal object detection model based on feature interaction and adaptive grouping fusion is proposed by combining deep learning algorithms with multimodal information fusion technology. The model uses infrared and visible object images as inTo improve the performance of object detection methods in complex scenes, a multimodal object detection model based on feature interaction and adaptive grouping fusion is proposed by combining deep learning algorithms with multimodal information fusion technology. The model uses infrared and visible object images as inputs, constructs a symmetrical dual-branch feature extraction structure based on the PP-LCNet network, and introduces a feature interaction module to ensure complementary information between different modal object features during the extraction process. Secondly, a binary grouping attention mechanism was designed. Global pooling combined with the sign function was used to group the output features of the interaction module into their respective object categories, and spatial attention mechanisms were used to enhance the object information in each group of features. Finally, based on the group-enhanced features, similar feature groups at different scales were extracted, and multi-scale fusion was carried out through adaptive weighting from deep to shallow. Object prediction was then achieved based on the fused features at each scale. The experimental results show that the proposed method significantly improves multimodal feature interaction, key feature enhancement, and multi-scale fusion. Moreover, in complex scenarios, the model exhibits higher robustness and can be better applied to different scenarios..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 468 (2025)
Improved Infrared Small Target Detection Algorithm Based on SSE-YOLO
Mei DA, Lin JIANG, Youfeng TAO, and Miao HU
To address the problems of a small infrared imaging area, low resolution, and ease of occlusion—resulting in incorrect detection, missed detection, and low detection accuracy—this paper proposes an infrared small-target detection algorithm based on SSE-YOLO. Firstly, a depth non-stepwise convolution module is introduceTo address the problems of a small infrared imaging area, low resolution, and ease of occlusion—resulting in incorrect detection, missed detection, and low detection accuracy—this paper proposes an infrared small-target detection algorithm based on SSE-YOLO. Firstly, a depth non-stepwise convolution module is introduced on the basis of YOLOv8s to avoid the loss of fine-grained information during the detection process and to improve the efficiency of feature learning. Then, a detection layer specialized for small targets is added in the feature extraction stage to improve the model's ability to extract infrared small targets. In addition, an efficient dual attention mechanism (EDAM) is designed to adaptively learn the importance of each channel and spatial location to better capture key information in the image. Secondly, the Shape_IoU loss function is used to focus on the shape of the boundary itself and its scale, which further improves the accuracy of boundary regression. Finally, a series of experiments were conducted on the FLIR dataset and a dataset captured by IRay. The results show that the average accuracies of the proposed method on the two datasets reach 89.8% and 92.1%, which are 3.3% and 2.9% higher than those of the original model, respectively..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 475 (2025)
Infrared Image Segmentation of Power Equipments Based on Improved Watershed Algorithm
Zhen WANG, and Lei LIU
When the watershed algorithm is applied to the infrared image segmentation of power equipment, the presence of image noise and gray-level variations caused by complex surface textures can lead to over-segmentation. To address this issue, an improved marked watershed algorithm combined with a K-means algorithm is proposWhen the watershed algorithm is applied to the infrared image segmentation of power equipment, the presence of image noise and gray-level variations caused by complex surface textures can lead to over-segmentation. To address this issue, an improved marked watershed algorithm combined with a K-means algorithm is proposed. First, the infrared image is preprocessed to suppress noise, and then combined with the gray-level information in the image. The equipment is extracted using the K-means clustering algorithm, and the resulting image is morphologically marked using an extended extremum transform based on the Otsu algorithm. Finally, the gradient image generated from the K-means clustering result is modified using the marked results to obtain the input for the watershed algorithm and complete the final segmentation. Experimental results show that the proposed method effectively reduces the sensitivity of the watershed algorithm to noise and gray-level variations, thereby overcoming the over-segmentation problem. Compared with the Otsu algorithm, region growing algorithm, and other classical methods, this approach segments only the external contours of the equipment while ignoring surface texture details..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 484 (2025)
Infrared Image Segmentation Method of Circuit Board Based on GAN-SUNet
Li WANG, and Xuan XIA
Infrared images can directly reflect the temperature of a circuit board and its changes. To address the challenge of accurately locating chips on infrared images of circuit boards, this paper proposes a segmentation method based on the GAN-SUNet model. The SUNet model is improved from the UNet model by introducing a spInfrared images can directly reflect the temperature of a circuit board and its changes. To address the challenge of accurately locating chips on infrared images of circuit boards, this paper proposes a segmentation method based on the GAN-SUNet model. The SUNet model is improved from the UNet model by introducing a spatial pyramid pooling (SPP) module, modifying the loss function, and reducing the number of convolution cores to enhance detection accuracy and network speed. First, a GAN is used to learn and train on collected infrared circuit board data to generate simulated infrared images and expand the dataset. Then, the generated dataset is used to train the SUNet model, and model parameters are adjusted to improve verification accuracy. Finally, the trained model is used to identify, detect, and segment chips on circuit boards, thereby achieving chip localization in infrared images. Experimental results show that for infrared image segmentation of circuit boards, the GAN-SUNet model achieves an average intersection and merging ratio of 93.77%, effectively reducing the burden of manual chip localization and providing strong support for subsequent chip temperature data processing..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 493 (2025)
Research Status and Development of Non-Line-Of-Sight Activeand Passive Imaging
Yurou CHEN, Youpan ZHU, Jiatong YU, and Aiping SUN
Recently, non-line-of-sight imaging has been presented as a novel imaging technology that can expand the human field of vision. Its operation is based on time-of-flight detection technology, which can detect photons reflected from objects outside the field of view, thereby reconstructing the images of hidden targets usRecently, non-line-of-sight imaging has been presented as a novel imaging technology that can expand the human field of vision. Its operation is based on time-of-flight detection technology, which can detect photons reflected from objects outside the field of view, thereby reconstructing the images of hidden targets using a reconstruction algorithm. This technology has significant application prospects in the fields of disaster relief, medical diagnosis, antiterrorism operations, and unmanned driving. The research status of active and passive non-line-of-sight imaging systems in recent years is briefly summarized, and their characteristics and development trends are analyzed for each imaging system. The paper also discusses some key issues that need to be addressed in the practical application of partial non-line-of-sight imaging technology along, along with prospects for the development of non-line-of-sight imaging technology..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 501 (2025)
Application and Research Progress of Infrared Thermography in Exercise Physiology
Xianxiang ZENG, Chunxue TANG, Yuxiao DENG, and Lijun SHI
Owing to its noncontact and lightweight characteristics, infrared thermography (IRT) has been increasingly recognized and applied in exercise physiology. This study combines a literature review and empirical research to investigate the patterns of skin temperature (Tsk) changes, the application status, and the physioloOwing to its noncontact and lightweight characteristics, infrared thermography (IRT) has been increasingly recognized and applied in exercise physiology. This study combines a literature review and empirical research to investigate the patterns of skin temperature (Tsk) changes, the application status, and the physiological mechanisms of constant-load endurance exercise, incremental load exercise, and resistance exercise. It also aims to construct a standardized process for IRT-based Tsk detection in exercise, considering factors that affect IRT temperature measurements, such as equipment, environment, individual differences, and analysis methods, to promote the practical application of IRT in the field of exercise physiology..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 510 (2025)
Micro Linear Stirling Cooler for HOT IR Detectors
Yun LUO, Jun CHEN, Wei HUANG, Jiapeng LI, Zhengrong ZHU, Enhe HUANG, Rong HUANG, Fanqin ZHOU, Yongxing RAO, Xiang BI, and Jinqing YANG
In response to the demand for low-power, small-size, lightweight, low-cost, high-performance, and fast-cooling cryogenic coolers for use with high-performance infrared detectors on light-load platforms such as hand-held thermal imagers and UAVs, Kunming Institute of Physics (K.I.P) has developed micro linear coolers foIn response to the demand for low-power, small-size, lightweight, low-cost, high-performance, and fast-cooling cryogenic coolers for use with high-performance infrared detectors on light-load platforms such as hand-held thermal imagers and UAVs, Kunming Institute of Physics (K.I.P) has developed micro linear coolers for higher operating temperature (HOT) IR detectors. The linear resonant compressor was studied to operate at 100 Hz to increase power density. Simultaneously, a pneumatic expansion design incorporating a back pressure chamber was achieved. After multiple rounds of optimization and iterative design, the development of the C351 cooler was completed. Performance system tests verified the advancement of the indicators, and the cooler has reached small-batch production capacity. The performance of the matching 640×512 HOT medium-wave infrared detector includes power consumption of less than 2 W (thermal load 180 mW@77 K@23℃), cooling time of less than 90 s, and a cooler weight of 217 g (drive control circuit: 12 g)..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 517 (2025)
Experimental Study on Multi-point Cooling of Single-Stage Pulse Tube Cryocooler
Ankuo ZHANG, Fang XIE, Wenhui YU, Yinan HAN, Chao XIONG, and Jing XIE
In single-stage pulse-tube cryocoolers, only the cooling performance of the cold head is often considered, whereas the cooling effects at the cold and hot ends of the cold finger, due to the existence of large temperature gradients, are often neglected. Experimental studies were conducted to maximize the cooling potentIn single-stage pulse-tube cryocoolers, only the cooling performance of the cold head is often considered, whereas the cooling effects at the cold and hot ends of the cold finger, due to the existence of large temperature gradients, are often neglected. Experimental studies were conducted to maximize the cooling potential of this type of cryocooler and to explore its applicability in multitemperature scenarios. The experiment was based on an 8W@80K single-stage coaxial pulse-tube cryocooler, with separate loads applied to the external and cold ends of the cold finger to simulate different temperature zones. The cooling performance of the pulse-tube cryocooler under different load conditions was measured by regulating the thermal load. Based on a comparison of the experimental data, the influence mechanism between key parameters, such as intermediate and cold-end cooling capacity, under different input powers was analyzed, and their potential interrelations were discussed. The experimental results showed that multi-temperature applications of single-stage pulse-tube cryocoolers are feasible when the intermediate cooling temperature and capacity remain constant..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 523 (2025)
Germanium-Based Infrared Thin Film Transmittance Stability Under Tropical Marine Environment
Qiaofang WANG, Chongwen WANG, Hongwei YE, Jian LIU, Yuping YANG, and Yuanrong ZHAO
To study the transmittance stability of germanium-based infrared films in tropical marine environments, two samples: germanium-based double-sided DLC film and germanium-based double-sided high-efficiency antireflective film, were placed in a tropical marine environment for a natural exposure test under a shed, with a tTo study the transmittance stability of germanium-based infrared films in tropical marine environments, two samples: germanium-based double-sided DLC film and germanium-based double-sided high-efficiency antireflective film, were placed in a tropical marine environment for a natural exposure test under a shed, with a test cycle of six months and a total of four cycles. The transmission spectrum and microscopic morphology of the test samples from each cycle were analyzed. The variation pattern of the samples over time was examined through transmission spectroscopy results, and the stability and change mechanism of the infrared thin film transmittance were studied through microstructural analysis of the film layer. The test results show that the transmittance of germanium-based infrared films does not change significantly during one testing period under the shed. The overall waveform of the film remains unchanged with increasing test time, although the crest shifts toward longer wavelengths. After four test cycles, the transmittance of the high-efficiency antireflective coating was significantly reduced, whereas the transmittance of the DLC membrane did not decrease significantly, indicating good stability in a tropical marine environment..
Infrared Technology
- Publication Date: May. 13, 2025
- Vol. 47, Issue 4, 530 (2025)
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