In the combustion process of aero-engines, excited-state free radicals such as OH*, NO*, and NH* emit faint self-chemiluminescence in the ultraviolet (UV) band, which changes rapidly with the progress of combustion. UV image intensifiers, featuring up to a million-fold electronic gain and nanosecond-level shutter speed, can capture the transient structure of the combustion flow field in the UV band, laying the foundation for the quantitative measurement and interpretation of the variation rules of combustion characteristics with multiple physical parameters. This paper summarizes the application of UV image intensifiers in optical diagnostics of aero-engine combustion, including passive optical diagnostic techniques for imaging OH* self-chemiluminescence, and active optical diagnostic techniques using laser excitation for OH imaging. Finally, in line with the requirements of high spatial and temporal resolution detection for new types of aero-engines, the development direction of UV image intensifiers in combustion diagnostics is pointed out.

An electron bombarded active pixel sensor(EBAPS) is a novel, digital low-light device characterized by its low power consumption, high sensitivity, and suitability for extreme low-light detection. This study begins with the principles of the EBAPS, focusing on the internal structure of the sensor's cathode and anode to elucidate the working process of the EBAPS from its input of optical signals to its output of digital images. This study further analyzes the structural features of the EBAPS optical system and, combined with a series of EBAPS products from the Intevac Corporation, reviews the development iterations and applications of the EBAPS. Finally, this study summarizes the various factors affecting the performance of EBAPS sensors and discusses the development trends of such devices.

An electron bombarded active pixel sensor (EBAPS) is a novel vacuum-solid, hybrid, digital, low-light night vision device. Flicker noise is a key factor affecting the resolution and image quality of EBAPS; however, there is currently insufficient research on the testing of flicker noise in EBAPS. Hence, this study conducted research on EBAPS flicker noise testing methods using connected domain detection algorithms to filter out high-brightness noise spot areas and proposed an adaptive, median replacement, discrete coefficient testing method for abnormal pixel points. Based on these results, an EBAPS flicker-noise testing system was developed using the discrete coefficient and number of bright noise spots as parameters to characterize the flicker noise. The system drives the EBAPS to transfer image data collected under different test conditions to an upper computer for noise processing and analysis. The test results indicate that the appropriate test illuminance is 1.27×10−3 lx. Moreover, the number of high-brightness noise spots is relatively low in the −1000−1300 V range, and it significantly increases when the voltage is between −1300−1500 V. The repeatability of the discrete coefficient and number of connected domains was within 3%, thus verifying the stability of the testing system and providing an effective means by which to test flicker noise in domestic EBAPS.

The development of image sensors has made it necessary to detect more dimensions of image information. Hence, a new polarization low-light structure was designed to solve the problem in which polarization units cannot be imaged under low-illumination conditions. The introduction of this new structural unit significantly improves the imaging quality of the device under low illumination and light conditions. We completed the production process of a polarized low-light structure and utilized multiple high-energy ion implantation and high-temperature annealing to form a saddle-shaped, “p”-shaped, longitudinal antiblooming structure to achieve the halo suppression of EMCCD devices. Finally, the imaging performance of the device was analyzed, and it was found that the imaging quality of the device hardly decreased under low-illumination conditions, while sufficient polarization information was obtained to achieve polarization detection of the target. This new polarized low-light structure enables image sensors to detect multidimensional information from targets under low-illumination and low-light conditions.

Reflectance recovery via the simultaneous estimation of reflectance and illumination is a prevalent and effective solution for image enhancement based on retinex decomposition, but its use results in a complex algorithm structure because reflectance recovery is formulated as a constrained optimization problem that cannot be solved via simple optimization techniques. In this study, a detailed saliency estimation method is proposed to recover reflectance from grayscale images via optimization employing gradient descent algorithms. This method is built on our hypothesis of dark region approximation (DRA). Because the illumination in dark regions of a low-light image is weak to the point of being negligible, the intensities of dark regions in the captured images are approximated as reflectance. The Gaussian field criterion is applied to establish a differentiable optimization function via DRA. This unconstrained optimization problem is then solved using the quasi-Newton method to estimate the detail saliency layer via the DRA-based retinex model. Finally, the reflectance is recovered from the detailed saliency layer. The results for a variety of images demonstrate the superiority of our method over several state-of-the-art methods in terms of enhancement efficiency and quality.

To compensate for the insufficient signal-to-noise ratio, which cannot be accurately localized in two-dimensional space to analyze the flicker noise characteristics of an image intensifier, this study designs a low-light image intensifier flicker noise test method based on a discrete coefficient and Harris corner point detection for the image intensifier flicker noise characteristics. In this method, a high-frame-rate image acquisition system based on a Gsense400BSI CMOS image sensor was used to realize flicker noise image acquisition that matched the afterglow time of the fluorescent screen of the image intensifier. By calculating the pixel-level discrete coefficients of the images acquired from consecutive multiframes, a hotspot map was visualized. In addition, the Harris corner detection algorithm was used to accurately analyze the flicker noise in each region of the fluorescent screen of the image intensifier and mark the bright noise spots on the fluorescent screen. The experimental results show that this method can realize the two-dimensional analysis and localization of the flicker noise of the image intensifier and thus provide technical support for the performance optimization of the image intensifier and testing of noise characteristics.

Images captured by complementary metal-oxide semiconductor (CMOS) cameras under low-light environments have problems, including low contrast, high noise, blurred details, and insufficient enhancement algorithms. Although CMOS cameras can improve image brightness, they do not consider how to retain the detailed information of the original image. Therefore, this paper proposes a detail-preserving low-light image enhancement method. First, each channel in the original low-light image was processed using an adaptive filter to improve the effect of noise on the image. Subsequently, a detail layer and a basic layer are obtained from the filtered image. The detail layer is used to preserve the texture of the image, and the basic layer is used to enhance its brightness. Moreover, the detail layer is obtained via coarse illumination and light components, whereas the basic layer brightness enhancement is obtained using the alpha algorithm to fuse the original image, gamma correction result, and gamma priori correction result. Finally, the luminance channels of the detailed and basic layers are fused to obtain an enhanced image. The experimental results showed that the average gradient and information entropy of the fused detailed image were significantly improved. In addition, among the five selected methods, the SSIM index was higher than those of other algorithms, indicating less distortion in the enhanced images. Good results were achieved for both the BRISQUE and PSNR indicators.

The Kunming Institute of Physics has achieved significant advancements in the directional growth technology of 150 mm cadmium zinc telluride (CZT) single crystals, thus enabling the small-scale production of 100 mm× 100 mm CZT substrates. The dislocation etch pit density (EPD) is ≤4×104cm-2, with precipitate dimensions of <5 m and a density of <5×103cm-2. In addition, 100 mm×100 mm large-area mercury cadium telluride (MCT) thin films were successfully prepared via the surface treatment of large-sized CZT substrates and tellurium-rich horizontal sliding-boat liquid-phase epitaxy. These films exhibit excellent surface quality, with thickness variation within ±1.25m and compositional variation better than ±0.0031. This achievement represents the largest area of CZT-based MCT thin films reported internationally and therefore provides a solid foundation for the development of 10 k× 10k or larger-scale infrared detectors and the mass production of 4 k× 4k scale infrared detector products.

With the development of infrared technology, cooled infrared detectors are playing an increasingly important role in gas detection. This paper introduces research on infrared gas detectors, domestically and abroad, and expounds on the recent research progress of Zhejiang Juexin Microelectronics Co., Ltd. on VOC gas detectors. The detectors were manufactured using a narrow bandpass filter design, stray radiation suppression, and detector assembly process technology. Moreover, a systematic performance evaluation and analysis of the detector were performed, and the actual imaging was displayed.

Micro-LEDs are a new display technology with advantages including high contrast, fast response, and long lifetimes. Micro-LEDs are currently regarded as an active topic of research. Micro-LED display technology is a promising industry, but its commercialization faces many technical challenges and bottlenecks. This study explores the diode preparation process and related technologies for high-brightness, green-light, GaN-based micro-LED micro-displays. Monochrome green micro-LEDs with resolutions of 800×480 and 0.41 in were fabricated based on the CMOS driver circuit of an all-digital signal circuit. The CMOS driver circuit was connected to an LED chip via high-precision flip bonding. The experimental results showed that the turn-on voltage of the LED was 2.8 V and that the peak wavelength of the electroluminescence spectrum was 524 nm. The maximum brightness of the device can reach 250,000 cd/m2 within the normal driving range of silicon-based CMOS circuits, and the brightness can reach 108,000 cd/m2 at 5 V. When the current density was controlled at 0.61 A/cm2, the CIE coordinates were (0.175, 0.756). When the current density was increased from 0.3 A/cm2 to 1.3 A/cm2, the CIE coordinates changed from (0.178, 0.757) to (0.175, 0.746). The color stability of the device met the requirements for practical applications.

Owing to industrialization and the rapid development of modern society, the leakage of dangerous chemical gases in industrial production seriously endangers the safety of human life and property. Effectively detecting the presence of contaminated gas and obtaining information on the gas concentration and distribution have become important topics in gas leakage detection. Uncooled Snapshot Infrared Video Spectrometer (USIVS) is an ideal hardware scheme that can directly perceive the existence of dangerous chemical gas from the image and obtain the position of dangerous chemical gas to provide strong support for emergency responses. However, the sensitivity and spectral resolution of commercial lightweight passive infrared spectral imagers are relatively limited, and it is difficult to accurately detect the presence of polluted gases using existing inversion methods. In this study, an infrared video spectral imager is introduced based on an uncooled snapshot and its applicable data-processing technology. The gas concentration inversion method is used to simulate gas at different temperatures and optical path lengths, and the inversion results are relatively accurate, with average errors of 2.88% and 0.61%, respectively. The gas concentration inversion method is tested in laboratory and outdoor settings. The results show that the algorithm has good stability with average errors of 6.18% and 7.47%. The effective combination of USIVS and data processing technology can quickly and accurately detect the presence of polluted gas and provide the gas concentration of each pixel in the image. This in turn can realize gas cloud concentration inversion, providing a reference for the commercialization and practical application of this technology in the future.

Infrared target detection algorithms play important roles in the military and civilian fields and have been widely studied. However, relatively few studies have been conducted on the use of dual-band images for targeted detection. To fully utilize the advantages of dual-band images in target detection, a fusion algorithm based on multiple features of infrared dual-band images was proposed through an in-depth analysis of the detection results. The proposed fusion algorithm utilizes a deep learning-based multi-feature fusion network to process the detection results of dual-band images, fully mine the feature information of the target, adaptively select the detection results of a single band as the output, and obtain the final decision-level fusion detection results. The experimental results show that, compared with using single-band images for object detection, the proposed infrared dual-band fusion algorithm based on multiple features can effectively utilize information from different bands, improve the detection performance, and fully leverage the advantages of infrared object detection equipment.

To enhance the visual perception of vehicles, an improved contour angle orientation (CAO) algorithm is proposed for the registration of infrared and visible light images in traffic scenes. By simulating different traffic scenarios, a performance comparison was conducted among mature algorithms to select the superior CAO algorithm. Subsequently, improvements were made to the coarse matching parameters and image preprocessing scaling procedure. Experiments demonstrate that the refined CAO algorithm achieves more precise fine matching, thus resulting in mosaic stitching with smoother transitions and lines and yielding better results. Compared with the original CAO algorithm, the improved version reduces the RMSE value by 3.29%, increases the precision value by 2.13%, and decreases the average computation time by 0.11 s, thereby demonstrating improvements in both registration accuracy and real-time performance.

The atmosphere and imaging height directly affect the infrared image quality of thermal imagers. Using the infrared image of an aircraft platform as the data source, infrared simulation images at different heights and atmospheric modes were studied, and a simulation calculation formula for the height of the thermal imager was derived. By selecting different atmospheric modes, examining MODTRAN and LOWTRAN atmospheric radiation transmission models for infrared image atmospheric correction at different heights, and analyzing and comparing the obtained simulation data, it is concluded that when the distance is less than 20 km, the simulation data of the two models in the same atmospheric mode are close and that the error is small, which is ideal. When the distance was greater than 20 km, the reference value of the LOWTRAN model simulation data was small, and the results of the MODTRAN model were closer to the actual situation and therefore more practical.