With the development of ultraviolet detection technology, oxide materials showing the unique advantages in the field of ultraviolet detection, which the traditional detectors didn't possess, and becoming a hot research topic in recent years. It is a fast-developing dual-purpose detection technology after the infrared detection technology. However, the wide applications of oxide-based ultraviolet detectors still face challenges. In this paper, we have summarized the applications and development histories of the ultraviolet detection technology at home and abroad. The crystal structures, properties and progresses in devices of three kinds of metal oxide ultraviolet materials are summarized and discussed. In the end, the problems in the research of the oxide-based ultraviolet detection materials and devices are analyzed, and the development of the oxide-based ultraviolet detection technology is summarized and prospected.

Driven by market demand, uncooled infrared bolometer arrays are gradually becoming popular in several fields, and their laser interference has become a major research topic. In this study, based on the structure and working principles of an uncooled microbolometer array, temperature response under laser irradiation is analyzed. An experiment of 10.6 μm continuous laser irradiation of an uncooled polysilicon detector shows that the pixel array enters different damage states. The laser power range and thermal effect mechanism of laser damage are also analyzed. Previous studies have shown that the interference area is larger than the spot area as a result of "heat inversion" and that the influence of laser transmission on the battlefield is equivalent to chopping modulation. T he effects of modulation frequency and duty cycle are also studied. Analytical results show that a continuous laser can achieve a better interference effect on an uncooled microbolometer with a low transmission modulation frequency and large duty ratio.

To meet the requirements of the micro-miniature air-to-air missile and solve the problem of not reaching full field angle, this paper presents a micro-miniature infrared seeker with roll-pitch structure, applying the integration philosophy of optical-mechanical structure and pitching shaft. Compared with the classic roll-pitch frame, this new structure combines two individual pitch shafts; additionally, the optical-mechanical structureusesonly one mechanical part, thus greatly reducing its size. Moreover, this new structure has a focus function that could improve the image quality. After structure design, we conducted thermo-mechanical coupling analysis on structure parts and lens under eight extreme conditions. The results show that the optical-mechanical structure meets the requirement of micro-miniature(80 mm), shock resistance (10g), and high low temperature test (-40℃~60℃). The simulated analysis can predict real conditions and has great guiding significance for optical-mechanical structure design.

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.

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.

Spectral technology is a promising prospect for highway state detection(whether frozen, water accumulated, or snow accumulated). However, there is little research on using sunlight as a light source to identify highway states. Sunlight and halogen tungsten lamps were used as experimental light sources in the day and night. Spectral curves of the visible-near-infrared bands of ice, water, snow, and highway backgrounds were obtained using a micro-spectrometer. During the day, the state of icing and stagnant water resulted in a phenomenon known as "Different substances with similar spectra" under different illumination conditions. Then, based on the characteristics of sunlight illumination, the solution of "environmental variables" as eigen values was proposed. The curve of the spectrum and the normalized "environmental variables" were combined into a new data waveform, and a neural network model based on Dropout and an Adam optimizer was established for training and recognition. The final recognition rate was 99.375%. At night, due to the evident differences in the spectra of various samples, the spectral curves of each sample were identified using the "combination-threshold" method. Experiments proved that the method of combining two light sources can effectively identify the road surface state.

Infrared thermometers are popular because of their safety, hygiene, and high efficiency. However, commercial infrared thermometers have large measurement errors and high cost, so their application is limited. Considering this, this paper first analyzes various factors that affect the measurement accuracy of an infrared thermometer and gives the calculation results of the specific influence degree. Then, using STM32F407 MCU as the control core, an MLX90615 infrared sensor, DS18B20 integrated temperature sensor, and HC-SR04 ultrasonic sensor to obtain information, a cheap and reliable portable infrared thermometer for hospitals and families is designed, and a method of temperature compensation is provided. Finally, the reliability of the system design was verified by testing. The test results show that the maximum comprehensive error is less than 0.15℃, which has definite practical value and reference value.

Dynamic range compression of infrared images is an important research direction in the field of infrared image visualization. The dynamic range compression algorithm directly determines the important visualization indexes of the original infrared image, such as detail retention and overall perception; in a sense, it is the basis and guarantee of detail enhancement. This study investigates a wide dynamic range compression algorithm and a local compression algorithm based on a global compression algorithm. Based on the two algorithms, we study and analyze the development process and the advantages and disadvantages to improve the research direction and development trend, which will provide a reference for researchers.

To ensure that researchers are well-informed regarding infrared image edge detection algorithms and to provide a valuable reference for follow-up investigations, we review relevant research conducted on infrared image edge detection algorithms in the past ten years. First, infrared imaging and edge detection technology are summarized, and then, the difficulties and challenges of infrared image edge detection algorithms are described. Finally, the main infrared image edge detection algorithms are summarized, and the related algorithms are divided into four categories: improved classic edge detection operator-based algorithms, ant colony algorithm-based algorithms, mathematical morphology-based algorithms, and network model-based algorithms. Considering traditional infrared image edge detection algorithms, the morphological method has potential because of its simplicity and ease of use; for non-traditional infrared image edge detection algorithms, the method based on deep learning has stronger pertinence, better robustness, and no requirement of designing complex algorithm steps, which brings new development opportunities to infrared image edge detection.

Eliminating non-uniformity is a persistent challenge for infrared imaging systems, especially when the integration time varies. This paper describes a non-uniformity correction method with the ability to adapt to arbitrary changes in integration time by correcting the infrared radiation flux map of the scene, which is estimated by pixel-wise radiometric self-calibration. Multiple images of an extended blackbody, obtained with different integration times and blackbody temperatures, were used to obtain the parameters of both the correction model and radiometric calibration model. The correction effect of this method within a wide range of integration times was verified by a high-resolution HgCdTe medium-wave infrared imager.

In infrared image processing, owing to technical issues with the infrared detector, the original infrared image includes a variety of noise, especially salt and pepper noise, fixed noise, or random stripe noise. Currently, there are many filtering algorithms for infrared image denoising, but they emphasize time, space, denoising effect, maintaining detail, and so on differently; therefore, it is difficult to achieve a perfect combination. Identifying methods to filter noise information more quickly, efficiently, and accurately and retain more details is an important future research direction for noise reduction in infrared image processing. This study investigated and compared the current mainstream infrared image denoising algorithms from three categories: traditional filter denoising, transform domain filter denoising, and image layered processing filter denoising, and a combination of a traditional algorithm and image layered adaptive denoising algorithm is proposed to provide a reference for future studies in related fields.

Super-second-generation and third-generation image intensifiers are two types of image intensifiers that use different technologies. Super-second-generation image intensifiers employ a Na₂KSb(Cs) photocathode, whereas third-generation image intensifiers employ a GaAs photocathode. Third-generation image intensifiers employ higher cathode voltages than those employed by super-second-generation image intensifiers. In addition, third-generation image intensifiers employ an antireflection coating between the glass input window and GaAs photocathode; however, this is not employed in super second-generation image intensifiers. Furthermore, third-generation image intensifiers employ ion barriers on their MCP(microchannel plate), whereas super-second-generation image intensifiers do not. In terms of limiting resolution, despite the small initial electron velocity, narrow exit angle distribution, and high cathode voltage of the third-generation image intensifiers, the limiting resolutions of the two types of image intensifiers are the same; the advantages of the GaAs photocathode of the third-generation image intensifiers have not been introduced under the existing limiting resolution level. In terms of signal-to-noise ratio, the GaAs photocathode has a higher cathode sensitivity, normally more than twice that of the super-second-generation image intensifier. Thus, theoretically, the third-generation image intensifiers have signal-to-noise ratios that are 1.4 times those of the super-second-generation image intensifiers. However, the two types of image intensifiers are basically the same owing to the influence of higher cathode voltage and ion barrier transmittance and the advantage of not introducing the high sensitivity of the GaAs photocathode of the third-generation image intensifiers. In terms of gain, although the third-generation image intensifiers have higher cathode sensitivity and cathode voltage, the super-second-generation image intensifiers compensate for the shortcomings of cathode sensitivity and cathode voltage by increasing the working voltage of the microchannel plate. Therefore, in terms of the existing image intensifier gain, the gains of the two types of image intensifiers are identical. In terms of equivalent background illumination(EBI), owing to the higher sensitivity of the GaAs photocathode, the third-generation image intensifiers can obtain lower equivalent background illumination under the same photocathode dark current. Therefore, the third-generation image intensifiers have higher initial contrast than that of the super-second-generation image intensifiers. The higher the initial contrast of the input image, the higher the contrast of the output image. In terms of halo, because the photocathode of the third-generation image intensifiers has high sensitivity and an ion barrier film, theoretically, the third-generation image intensifiers have higher halo brightness than that of the super-second-generation image intensifiers. However, in actual situation, the halo brightness levels of the two types of image intensifiers are basically the same. In terms of stray light, the GaAs photocathode has an antireflection coating; thus, the stray light is lower than that of the super-second-generation image intensifier, so the imaging of the third-generation image intensifier is clearer and the sense of gradation is better. In terms of spectral response beyond the long-wavelength threshold, because the spectral responses beyond the long-wavelength threshold of the super-second-generation image intensifiers are higher than those of the third-generation image intensifiers, the super-second-generation image intensifiers have better imaging performance than that of the third-generation image intensifier under supplementary illumination using the near-infrared waveband. For example, without the presence of any light, the super-second-generation image intensifiers can obtain better images at a supplementary illumination of 980 nm wavelength, whereas the third-generation image intensifiers cannot. In terms of the resolution of low illumination, the super-second- and third-generation image intensifiers with similar performance parameters have the same low luminance resolution. It should be noted that this conclusion was obtained under the test conditions of a standard A light source. When the actual environmental emission spectrum distribution is different from that of a standard illuminant A, the low illumination resolutions of the two types of image intensifiers are different. Photocathode sensitivity is a parameter of the photocathode and not of the image intensifier. Thus, the performances of the two types of image intensifiers cannot be compared in terms of photocathode sensitivity. The difference between the super-second and third-generations cannot be understood using the meaning of "generation; " their differences do not lie in the meaning of "generation."

It is difficult to directly distinguish the human body area identified by the infrared data measured by medical infrared thermal imaging equipment from the temperature data obtained by conversion. It is often necessary to convert it into image data and use image processing technology to obtain the region of interest and the biological characteristics from the temperature data in the given area. Accordingly, disease screening or diagnosis can be realized. However, conversion from 14-bit infrared data to 8-bit image data incurs a serious loss of data accuracy, resulting in poor processing performance. In this paper, a new expression method for thermal images is proposed. The obtained color thermal image contains the original precision temperature data information and the color enhancement effect under the setting scale of the temperature observation window. At the same time, it contains the temperature data record and the setting rules of the observation window. Through the inverse transformation of the image data, the original temperature data can be reproduced and the color enhancement effect can be changed. The thermal image provided by this method can be used in different infrared thermal image systems without requiring additional access to temperature data files. This will be more aligned with the development trend of big data and artificial intelligence.

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.

With respect to the complexity and variety of infrared image noise, it is necessary to consider the detailed enhancement of images while suppressing noise. Accordingly, this study developed an infrared image denoising algorithm using the rough set theory. Collected infrared images were first layered by guided filtering. Then, further multi-dimensional stratification was conducted using the rough set theory, and output images were obtained through merging and restoration. Compared with a subjective observation and an objective evaluation index, the algorithm was effective in infrared image denoising and helped to enhance weak and small target details. In addition, the algorithm showed low complexity and good real-time performance. It thus has good application prospects in engineering implementations.

Evasive maneuvers and decoy deployment are effective measures against infrared (IR) air-to-air missiles for fighters. In this study, both aspects were considered: barrel roll maneuver and unpowered point source decoys. For practical purposes, the interference process, movement characteristics, and influence mechanism of the decoy on the missile guidance system are expounded, in which the conditions needed for the barrel roll maneuver and the force of the decoy are considered. In addition, the air-to-air missile is assumed to adopt the true proportional navigation law or augmented proportional navigation law, and the decoys are launched in the conventional mode or emergency mode. Linearized time-varying models and adjoint models for barrel roll maneuvers with decoy deployment influence on missile guidance precision are established. The correctness of these models was verified by a simulation result analysis and comparison. The miss distance is an important parameter for characterizing the performance of an air-defense missile. The average miss distance and percentage of maximum miss distance were proposed to analyze the adjoint model results. Based on the work mentioned above, the barrel roll rate and the transition step maneuver angle of the target aircraft, as well as the simultaneous launch quantity, the period between successive launches, and launch direction policy on the miss distance are analyzed to provide strategic references for fighters against IR air-to-air missiles.