The rise of blocked impurity band (BIB) infrared detectors based on germanium and silicon has promoted the rapid development of infrared astronomy, among which silicon-based BIB infrared detectors with specific wavelengths play an irreplaceable role in the aerospace field. Research on silicon-based BIB infrared detectors has been conducted abroad for more than 40 years, and many of its applications in the astronomical field have been realized by NASA and its related research institutes. However, domestic research on silicon-based BIB infrared detectors is still in its infancy. In this paper, the working principle of silicon BIB infrared detectors is described first; then, the structure and fabrication process of the device are briefly summarized, the performance of different types of silicon BIB detectors is compared and analyzed, and its application in astronomical detection is described. Finally, the future development of silicon BIB infrared detectors is discussed.

To address the problems of color fading and low contrast in underwater images caused by the complex imaging environment in the ocean, improved Multi-Scale Retinex with Color Restore (MSRCR) and Contrast Limited Adaptive Histogram Equalization (CLAHE) multi-scale fusion algorithms for underwater image enhancement are proposed. First, the MSRCR algorithm with guided filtering was used to solve the problem of underwater image color fading. Second, the CLAHE algorithm with Gamma correction was used to improve the contrast of underwater images. Finally, the improved MSRCR and CLAHE images were fused at multi-scale to obtain an underwater image with enhanced detail. The experimental results show that, compared with other algorithms, the Peak Signal-To-Noise Ratio (PSNR) of the proposed algorithm is improved by 9.3914 on average, and the Structural Similarity Index Measure (SSIM) and Underwater Image Quality Evaluation (UIQE) increased by 0.3013 and 4.7047 on average, respectively, which can realize the effective enhancement of underwater images.

To solve the problem that a single tracker cannot effectively deal with the complex background and significant changes in target appearance, leading to the problem of low accuracy of thermal infrared target tracking, a tracking algorithm based on a fully-convolutional Siamese network is proposed for thermal infrared tracking. First, a pre-trained convolution neural network is used to extract the features of multiple convolution layers of thermal infrared targets and select channels. On this basis, three corresponding trackers are constructed, and each tracker performs tracking independently and returns a response map. Then, the Kullback Leibler (KL) divergence is used to optimize and integrate multiple response maps to obtain a stronger response map. Finally, the integrated response map is used to determine the target location. To evaluate the performance of the proposed algorithm, experiments were conducted using the most comprehensive thermal infrared tracking benchmark, LSOTB-TIR. The experimental results show that the proposed algorithm can adapt to complex and diverse infrared tracking scenes, and its comprehensive performance is better than that of existing infrared tracking algorithms.

Infrared images play an important role in the condition monitoring and fault identification of power equipment. Aiming at solving the problems of low resolution and low definition in the application of infrared images, this paper proposes a super-resolution method for compressed infrared images of sensing power equipment based on the prior constraint of the image gradient ratio (GNR). The GNR prior was introduced into the traditional compressed sensing super-resolution model by analyzing the variation in high-frequency information of power equipment infrared images at different sampling ratios. An effective algorithm was designed to solve the improved model. By introducing auxiliary variables into the semi-quadratic splitting method, different variables were iteratively and alternately solved to realize the super-resolution reconstruction of infrared images. The simulation results show that the introduction of GNR prior information was conducive to the super-resolution algorithm achieving better reconstruction. Compared with existing classical super-resolution methods, the proposed method improves both the subjective visual effect and objective evaluation index.

To realize environmental thermal image monitoring in a large area, this study took a university training field in Chongqing as an example to investigate UAV regional environmental thermal image monitoring technology. First, the UAV was used for environmental thermal image acquisition, and the Agisoft Metashape software was used for UAV thermal infrared mosaic thermal image processing. The processed thermal infrared images were used for environmental thermal image monitoring and target analysis. Experiments showed that the technology can realize fast processing of regional thermal infrared images, and the processing results can provide an effective reference and basic data for environmental thermal image monitoring and target thermal image analysis.

In criminal and civil cases, signatures, dates, numbers, and other handwritings of several important documents are deliberately covered to conceal the real information such that they cannot be used as evidence. Therefore, it is necessary to study the feasibility of hyperspectral imaging technology (approximately 450–950 nm) for rapid and non-destructive identification of covered handwriting. Black handwriting pens are mostly used such that two pens are randomly selected from 21 kinds of black handwriting pens to cover each other as samples. Simultaneously, two kinds of black handwriting pens with carbon in the ink and two kinds of black handwriting pens without carbon in the ink are selected, and the same pen is used to write and cover by itself as a sample. The experimental results show that most of the covered handwriting can be completely and clearly identified using hyperspectral imaging technology in the band of approximately 450–950 nm with the real shape and information, which has a good effect. Part of the identification effect is not good, and the details of the original handwriting are incomplete, but the original handwriting can be recognized. In addition, few parts are blurred, which cannot meet the identification requirements. However, most of the covered handwriting is difficult to develop using the traditional infrared method.

Aiming at the requirements of target drone applications, modeling and simulation, outfield testing of infrared radiation characteristics of target drone in flight is necessary, and the results have high confidence level. In this paper, the radiation intensity distribution of the target drone in different azimuth at night is obtained by calibrating the infrared measuring equipment infrared imaging measurement equipment, calculating the path radiation and transmittance, and radiance retrieval. The measurement error is about 21.24%. The radiation intensity is affected by other factors. When the target drone is flying around the equipment, the radiation intensity in different azimuth is basically the same. Tail flame is difficult to detect in long-wave infrared band. In the characteristics simulation and modeling of target drone, the influence of tail flame radiation has little effect. At this distance, the gray contrast between the target and background is only about twice the contrast response threshold of eye. The target drone is hard to track by manual detecting. It should be paid attention to the influence of contrast in the characteristics simulation of target drone. The research results of this paper can provide support for characteristics simulation and modeling of target drone and development of infrared measuring equipment.

Aiming at the problems of incomplete contour information, missing edge and texture details in infrared and visible image fusion, A Improved Simplified Pulse Coupled Neural Network (MSPCNN) and Fuzzy C-mean (FCM) image fusion algorithm is proposed. First, infrared and visible images were decomposed into high and low frequency sub-bands using the Non-Subsampled Shearlet Transform (NSST).Then MSPCNN is used to fuse the decomposed high frequency subband, and a Gaussian distribution weight matrix is used for processing to enhance the detail information and contrast. Then, the obtained low-frequency sub-band images were extracted by using FCM clustering algorithm, and the approximate threshold of clustering center was set to simplify the process to achieve background classification extraction.Finally, the inverse transformation of NSST is carried out to complete the infrared and visible image fusion process.Through objective evaluation index calculation, compared with other algorithms of the same type, the method proposed in this paper has been improved in terms of average gradient, standard deviation, average similarity and other reference indexes. As the running speed of simplified algorithm of model parameters has been improved, the timeliness of the algorithm in this paper has been improved compared with other algorithms, and the algorithm is more suitable for complex scenarios.

Ceramic packaging is the most common packaging form used for uncooled infrared detectors. The low cost, miniaturization, and high reliability of packaging are its key development directions. This paper proposes an optimized design that can reduce the cost and volume by nearly 5% and 30%, respectively, compared to an existing ceramic packaging structure. First, the independence of the grid number is proved. Then, the maximum equivalent stress and maximum deformation of each component of the original and optimized structures of the uncooled infrared detector ceramic packaging were analyzed under two conditions: a 10.2G random vibration and a 500g half-sine wave shock employing ANSYS Workbench. The results show that both structures meet the reliability requirements. In addition, reliability simulation for different materials and different thicknesses of the infrared window of the optimized structure was conducted under a 500g half-sine wave shock condition. The results show that both germanium and silicon windows with thicknesses from 0.3 mm to 1.0 mm meet the reliability requirements, and there is a negative correlation between the thickness of the window and maximum equivalent stress, as well as maximum deformation. For infrared windows with the same thickness, the reliability of the silicon infrared window was better. This study provides a reference for the subsequent structural design and simulation calculation of the ceramic packaging of an uncooled infrared detector.

The existence of porosity defects on the weld surface reduces the effective cross-sectional area of the workpiece and the ability of the workpiece to resist external loads, which leads to workpiece fracture in serious cases. Therefore, a multi-defect detection method for weld surfaces based on eddy current pulse thermography technology is proposed. First, a new electromagnetic sensor structure is adopted to detect carbon steel defects with different diameters and depths through the principle of eddy current pulse thermography, and the temperature signals of the defect and non-defect areas in the image sequence are analyzed. To improve the sensitivity of the detection system, principal component analysis (PCA) is used to reconstruct the image sequence and enhance the defect features in the original image. Finally, the proposed method was verified experimentally. The experimental results show that this method can reduce the influence of the weld edge effect, realize large-area detection of weld surface defects, and provide an open field of vision for infrared thermal imaging.

To solve some problems in the determination of substance optical constants by spectral inversion, based on the traditional double thickness transmittance model, spectral transmittance equations with thicknesses of L and 2L are established. The eighth-order polynomial equation related to the attenuation coefficient is obtained through an algebraic operation. Real roots greater than 0 and less than 1 are solved to calculate the attenuation coefficient and extinction coefficient. Then, the quadratic equation with one unknown quantity about the interface reflectivity is solved, and the roots greater than 0 and less than 1 are selected to calculate the refractive index. In the process of determining the optical constants, the new method has no inversion error or iterative calculation time-consuming problems. The reliability of the new method is verified using the known optical constants of heptane from the literature, and the influence on the calculation results was analyzed when the double thickness does not satisfy the double relationship. In conclusion, when the relative error of the second thickness 2L was no more than 1%, the calculation error of the extinction coefficient was no more than 2.03%, and when three strong absorption points were not considered, the calculation error of the refractive index was no more than 1%.

During the entire work process, the frequency accuracy of input sine AC power directly affects the vibration of the linear Sterling refrigerator. Especially for single -piston linear Sterling refrigerators, the input sine AC electro -frequency accuracy will directly affect the vibration, reducing performance of the dynamic vibrator connected. Based on the research on the linear Stirling refrigerator inverter, through the analysis of the SPWM wave generation method, the MCU clock frequency in the inverter circuit, the cut-off frequency in the filter circuit, capacitance and inductance, etc., the relationship between the number of switches and frequency accuracy is obtained. According to the requirements of the actual application, the error between the actual output frequency of the linear Stirling refrigerator inverter and the target frequency must be less than ± 0.1Hz, and the frequency accuracy needs to be controlled within ± 0.1 %. Therefore, under this application conditions, when the MCU frequency is 72 MHz, the number of switches that meets the requirements is found to be between 1400-2400, and corresponding frequency accuracy is less than <± 0.1%.

Infrared digital holography has strong real-time performance, is not easily disturbed by visible light, and can be detected in complex environments. It is widely used in special fields. For example, dust aerosols in a blasting environment have strong absorption and scattering effects on visible light, and infrared light at the wavelength of the ”atmospheric window” in the infrared band is less affected by aerosols. This advantage has been combined with digital holography. A smooth cement plate of moderate size was fixed on a three-dimensional force application frame as the research object, and the infrared digital holography method was used to change the dust concentration in the environment. The stress field changes of smooth cement plates under different pressures were measured, and the feasibility of this method was verified by comparing holograms and phase differences. Visible light digital holography was used as a control experiment. The results show that infrared digital holography can measure the force application point, relative pressure, and stress influence area of the stress field in an environment of high-concentration dust and realize real-time, nondestructive, and full-field detection, while visible digital holography in this environment is poor or even unable to complete the detection. The method proposed in this paper significantly expands the practicality of the stress detection method based on digital holographic interferometry.