Remote Raman spectroscopy is used primarily for on-site rapid detection of dangerous goods, contraband, and deteriorated food from a safe distance. Early applications of remote Raman spectroscopy used visible or near-infrared lasers to excite the Raman spectrum. Such experiments were often conducted in the laboratory or at night, to avoid the influence of environmental light. Recently, solar-blind ultraviolet Raman spectroscopy has been widely used because of its advantages compared to visible or near-infrared approaches. Their advantages include a strong resonance effect, lack of interference from ambient light, and relative safety for the human eye. This study reviews the development of remote visible or near-infrared and ultraviolet Raman spectroscopy based on the analysis of the basic principles in natural environments. The advantages of remote ultraviolet Raman spectroscopy in the fields of anti-terrorism, drug control, and food safety are highlighted. The current challenges and development trends in remote Raman spectroscopy in natural environments are summarized.

In this study, the formation of a position-dependent conductivity transition in Cd_1-xZn_xTe crystals is investigated. The results indicate that the transition from p- to n-type Cd_1-xZn_xTe (x = 0.04) can be ascribed to the formation of the V_Cd-Cd_i interface. Cd vacancies (V_Cd) are easily generated in the Te-rich condition crystal growth process and are responsible for the p-type conductivity. However, Cd vacancies are filled and the n-type defect, Cd interstitial (Cd_i), form in the Cd-rich condition. This leads to the transition from p-type to n-type conductivity during the growth of Cd_1-xZn_xTe (x = 0.04).

In active infrared thermography technology, the extraction of defect information from infrared images is crucial. Traditional image processing methods can eliminate noise and improve image contrast, but several challenges remain, such as selecting the infrared image manually, subjectivity in the process of infrared image enhancement and segmentation, and information loss in the process of a single infrared image. To overcome these challenges, this study proposes a method for extracting defect information from infrared images based on time sequence information. First, concrete blocks with delamination are fabricated by indoor experiments. Then, active infrared thermal image detection technology is used to collect the infrared image data and temporal information is extracted for each pixel. Finally, the K-means method is used for defect feature extraction based on temporal information. The results show that the defect extraction method based on temporal information can extract hidden defect information. Furthermore, its hierarchical defect information extraction effect is better than that of the K-means method based on the spatial domain.

Owing to different imaging mechanisms, infrared images represent typical targets by pixel distribution, whereas visible images describe texture details through edges and gradients. Existing fusion methods fail to adaptively change according to the characteristics of the source images, thereby resulting in fusion results that do not retain infrared target features and visible texture details simultaneously. Therefore, a multi-feature adaptive fusion method for infrared and visible images is proposed in this study. First, a multi-scale dense connection network that can effectively reuse all intermediate features of different scales and levels, and further enhance the ability of feature extraction and reconstruction is constructed. Second, a multi-feature adaptive loss function is designed. Using the pixel intensity and gradient as measurement criteria, the multi-scale features of the source image are extracted by the VGG-16 network and the feature weight coefficients are calculated by the degree of information preservation. The multi-feature adaptive loss function can supervise network training and evenly extract the respective feature information of the source image to obtain a better fusion effect. The experimental results of public datasets demonstrate that the proposed method is superior to other typical methods in terms of subjective and objective evaluations.

The infrared image of a substation is significantly disturbed by noise and the texture information is unclear. Therefore, stitching traces or the ghosting phenomenon may appear in the process of stitching. To overcome these challenges, this study proposes an infrared image splicing method that improves the best seam-line. First, this method uses the SIFT algorithm to extract the image area features to achieve image registration, then introduces local weight coefficients in the overlapping area of the two images. Subsequently, morphological operations are performed on the intensity of the image color difference, which reduces the noise interference of the infrared image and improves the texture information of the energy function graph. Finally, dynamic programming is used to improve the seam-line search criteria and search for the best seam-line in the image overlapping area. The experimental results show that compared with the gradual fusion method and the best seam-line method, the average gradient, image clarity and image edge strength of the stitched image are improved, the transition of the fusion region is smoother and more natural, and the stitching trace is significantly reduced.

Original infrared images have a low contrast and high dynamic range, with the dynamic range varying between scenes. To obtain better images, it is necessary to transform the original infrared image data. Aiming to overcome the deficiency of the global histogram equalization algorithm, this study proposes a histogram equalization method based on region segmentation. By dividing the image into several regions, each region is histogram balanced; subsequently, pixels are reconstructed by linear interpolation. This effectively improves the image quality of the infrared thermal imaging system, greatly enhancing the contrast and image detail information. The algorithm is simple to implement in an FPGA and positive results are obtained.

Blind pixels often appear in infrared focal plane arrays owing to the influence of the manufacturing technology. The previously used single-band blind element compensation algorithm is not satisfactory for large blind clusters and blind pixels at edge positions. With the rise in double-band thermal images, a blind element compensation algorithm based on double-band information is proposed in this study. This algorithm combines the information from the two bands. Different strategies are used to compensate for the blind pixels in the image, according to the similarity of the neighborhood information of the two bands. This can effectively compensate for the large blind clusters in the image and the blind pixels at the edge using different strategies.

The fusion image must be made more suitable for human visual perception and the problem of a poor fusion effect caused by light and weather must be solved. Therefore, this study proposes a fusion method of visible and infrared images based on a rolling guidance filter. First, guided filtering is used to enhance the content of the visible image. Then, a rolling guidance filter is used to decompose the visible and infrared images into small-scale, large-scale, and base layers. In the process of information synthesis of large-scale layers, the weighted least square fusion rule is used to solve the problem caused by different features of visible and infrared images, and to improve the visual effect of fusion images. In the process of fusion of the base layer, the optimized fusion rule of the visual saliency map is used to reduce the loss of contrast. Finally, the large-scale, small-scale, and base layers are merged into a fused image. The experimental results show that the proposed method improves the visual effect, detail processing, and edge protection.

A falling liquid film (FLM) method for suppressing the vertical infrared of military targets under constant heat flux boundary conditions is analyzed in detail. A flow and heat transfer model of a laminar falling film is established. The temperature distribution on the falling film surface is obtained using the energy conservation method and omitting the liquid film inlet effect, which simplifies the solution process. By comparing the results of different studies, the effectiveness of the energy conservation method for evaluating the heat transfer process of a falling film in a fully developed section is verified. The recognition distance of the detector to the target is calculated using liquid film infrared suppression technology. The results show that increasing the flow rate and sufficiently controlling the inlet temperature of the liquid film enhances the infrared suppression effect on a specific target. The research methods and conclusions of this study have important applications in providing a point of reference for infrared suppression of military targets.

An infrared seeker refrigeration gas supply test system is used to determine the cooling time of an infrared seeker in a weapon system to verify the cooling effect of high-pressure. This study introduces the composition and structural design of the system by primarily using high-pressure argon as the refrigeration gas source. Argon controls and simulates the actual working temperature of the seeker through a high- and low-temperature test system, thereby controlling the cooling time, pressure, temperature test, and imaging display through the data acquisition system. To overcome common problems of systems in engineering applications, structural improvement schemes are proposed. Through several years of production and application, it is verified that the system can meet the requirements of batch testing for infrared seekers in weapon systems.

The complex and harsh thermal environment of low-orbit satellites necessitates strict requirements for the performance of the optical-mechanical structure of remote sensing cameras. In this study, an integrated opto-mechanical-thermal simulation analysis method based on an on-orbit temperature field is proposed by using a low-orbit satellite camera as an example. Thermal desktop, MSC Patran/Nastran, and Code V are used to construct the thermal, structural finite element, and optical analysis models, respectively. The structural deformation characteristics, including the shift, tilt, and distance of each mirror in the most extreme conditions of single camera imaging time, are obtained. Changes in the MTF of the optical system are analyzed and the primary influencing factors of the system transfer function are determined. Subsequently, optimization design is performed based on the structural parameters of the primary force-taking structure. The optimization results show that the thermal characteristics of the system are optimal when the linear expansion coefficient of the primary force-taking structure ranges from 5.0e-6 to 5.5e-6, and the system transfer function meets the target requirements.

In order to realize the static centroid balancing of missile borne infrared cameras, a set of counterweight load combination with less quantity, light weight, fine technology and interchangeability is designed under requirements of the whole machine quality. In order to design the counterweight load quickly and efficiently and arrange the installation position of the load combination reasonably for the missile borne infrared camera with small space volume, a method is proposed to simulate the centroid position of the original prototype by using the three-dimensional design software Creo4.0, and then calculate the coupling relationship between the mass of the counterweight load and the centroid position by using the torque balance principle at two points of the space. On the basis of summarizing the design principles of counterweight load, the counterweight load scheme is designed by using creo4.0. After projection, processing, assembly and strict centroid test, the results show that the method can achieve the centroid balancing function well, and make the missile borne infrared camera meet the centroid requirements. Compared with the trial method, this static centroid balancing method has obvious advantages of high efficiency and reasonable layout.

The reliability of thermal imagery has direct impact on the success rate of user tasks, maintenance costs and life cycle, so its reliability design is increasingly concerned. At the same time, as far as the development of thermal imagery in China is concerned, the reliability of the developed prototype does not reflect the reliability level of the products produced in small batches. Therefore, in order to fully reflect the reliability level of the developed prototype, this paper develops a method for certain infrared thermal imager that analyzes the feature of reliability growth in the development stage. We analyze the faults of the infrared thermal imaging camera, establish the mission reliability model of the infrared thermal imaging camera, propose corresponding improvement measures, and adopts the reliability to verify the effectiveness of the proposed measures. This method meets the requirements of equipment test and appraisal, and can achieve the goal of increasing the reliability of thermal imaging cameras and not reducing the reliability of batch products.

To improve the accuracy of infrared detection and realize synchronous detection of defect depth and size, a conjugate gradient recognition algorithm is integrated with pulsed thermography and pulsed phase thermography. Quantitative identification of infrared technology is achieved based on the phase and surface temperatures. The influence of these factors on the identification result is analyzed using numerical examples. The results show that without temperature errors, the defect is accurately identified based on the phase and surface temperature. The random temperature error decreases the accuracy of the identification result based on the phase and surface temperature. The uniform temperature error decreases the accuracy of the identification result based on the surface temperature. However, the uniform temperature measurement error does not affect the identification result based on the phase.