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.

In the Fourier transform spectrum detection technology of atmospheric composition and content detection, the output current signal of infrared detector is generally very weak. In this paper, a multi-channel weak current signal high-precision acquisition circuit is designed by analyzing the source of system noise, using high-precision and low-noise integrated operational amplifier, and reasonably selecting circuit parameters. An analysis of the circuit performance shows that the system can accurately acquire the nA level 1kHz current signal, and meet the requirements of weak signal detection.

A membrane diffractive athermal infrared optical system is designed. The optical system has an aperture of 200 mm, a focal length of 200 mm, a relative aperture of 1, a full field angle of 3., and a working wavelength of 10.7-10.9.m. The system uses the membrane diffractive lens as the primary lens, with the thickness of a micron, and has the advantages of large aperture and light weight, which solves the contradiction between the weight and the aperture of the existing infrared optical system. A hybrid refractive diffractive lens with a diffractive surface is used to correct the strong dispersion of the primary lens, effectively solving the problems of small field of view and narrow spectral range of the membrane diffractive primary lens. The use of membrane diffractive primary lens and refractive diffractive hybrid lens effectively utilizes the good athermalization characteristics of the diffractive surface. Combined with the selection of lens materials, it plays a good role in the athermalization of the optical system; the use of the diffractive surface increases the degree of freedom in the process of system design optimization. Membrane diffractive athermal infrared optical system has the advantages of light weight, good imaging quality, and excellent athermalization performance, which has a good application prospect in the field of infrared remote sensing imaging detection.

Because the traditional kernel correlation filter algorithm for visual object tracking has low tracking accuracy under fast motion, background clutter, and motion blurring conditions and cannot deal with scale changes, a real-time object tracking algorithm based on context awareness and scale adaptation is proposed. Based on the kernel correlation filter algorithm framework, context-aware and scale-adaptive methods are introduced to add background information and handle changes in the scale of the target. First, the target region is sampled using the features of the fusion histogram of oriented gradient (fHOG), color names (CN), and gray, and a two-dimensional translation filter is trained. Then, a scale pyramid is established in the target area and multi-scale sampling is performed using fHOG on the target area. Following this, a one-dimensional scale filter is trained. Finally, the update strategy is improved in the model updating stage. The experimental results of 100 sets of video sequences in the standard OTB-2015 dataset show that the proposed algorithm showed an improvement in the accuracy by 13.9% as compared with the benchmark algorithm (kernel correlation filter, KCF), and the success rate improved by 14.2%, which is superior to that of other comparison-tracking algorithms considered in the experiment. Under the conditions of scale change, motion blur, and fast motion, the proposed algorithm can maintain a high speed with accurate tracking.

The backbone of a convolutional neural network global branch, a residual network (ResNet), obtains low-resolution feature maps at side outputs that lack feature representation. The local branch aggregates the feature maps in the global branch, which are not fully learned, resulting in a negative impact on image segmentation. To solve these problems in GLNet (Global-Local Network), a new semantic segmentation network based on GLNet and High-Resolution Network (HRNet) is proposed. First, we replaced the original backbone of the global branch with HRNet to obtain high-level feature maps with stronger representation. Second, the loss calculation method was modified using a multi-loss function, causing the outputs of the global branch to become more similar to the ground truth. Finally, the local branch was trained independently to eliminate the confusion produced by the global branch. The improved network was trained and tested on the remote sensing image dataset. The results show that the mean absolute errors of the global and local branches are 0.0630 and 0.0479, respectively, and the improved network outperforms GLNet in terms of segmentation accuracy and mean absolute errors.

To address the low accuracy and slow speed of the traditional adaptive Canny algorithm in selecting the threshold value, an improved algorithm is herein proposed. The proposed algorithm utilizes the Otsu and fast fireworks algorithm (FFWA) to automatically set the high and low detection thresholds and the connecting edges. Consequently, the explosion radius, the production method, and selection strategy are improved as compared to those of the traditional fireworks algorithm, thereby increasing the speed and accuracy of the Otsu calculation. The experimental results show that the calculation speed of the fast fireworks algorithm increased by 36% as compared to that of the traditional fireworks algorithm. Moreover, the stability also increased considerably. The improved adaptive Canny algorithm not only maintains the same precision but also decreases the calculation time by 49%. This makes the result of edge detection of aircraft skin infrared images more ideal.

In the traditional image fusion method based on sparse representation, image blocks are used as units for dictionary training and sparse decomposition. The representation ability of dictionary atoms for image features is insufficient if the internal connection between the image blocks is not considered. Moreover, the sparse coefficients are inaccurate. Therefore, a fused image is not desirable. In view of the abovementioned problem, this paper proposes a fusion method based on the group K-means singular value decomposition (K-SVD) for visible and infrared images. Considering the image non-local similarity, this method constructs a structure group matrix using similar image blocks, and then, dictionary training and sparse decomposition are performed in the units of the structure group matrix by group K-SVD. Thus, this method can effectively improve the representation ability of dictionary atoms and the accuracy of the sparse coefficients. The experimental results show that this method is superior to the traditional sparse fusion method in terms of subjective and objective evaluation.

Autofocus technology plays an important role in the field of infrared thermal imager monitoring. At present, there exist some problems with infrared auto focusing technology, such as low success rate, complex architecture and low focusing speed. Therefore, this study proposes an auto focusing technology of infrared lens based on FPGA, which realizes the functions of infrared image processing, display, and auto focusing with a single FPGA. In view of the common characteristics of vertical stripe noise and random noise in infrared images, this study improves and optimizes the infrared definition evaluation algorithm and mountain climbing algorithm in the focusing process. The experimental results show that the algorithm and implementation method proposed in this study can help infocusing on the infrared lens remarkably. Meanwhile, the proposed method has characteristics such as high integration, fast focusing speed, and high success rate, and thus has wide application prospects.

In this paper, transmission spectroscopy was used to measure the spectral curve of Diamond-like carbon film on Ge substrate. By using the measured spectral curve and simulated annealing algorithm, the objective optimization function was constructed, and the thickness, refractive index and extinction coefficient of the film are obtained by spectral inversion. Compared the optical parameters of Diamond-like carbon film on Ge substrate obtained by this method with the measured results of ellipsometer, the error of refractive index is less than 1%, the error of thickness is less than 2%. In addition, the optical parameters of the film were brought into the theoretical calculation model of transmittance. Compared with the actual measured curve, the error of the transmission spectrum curve of Diamond-like carbon film on Ge substrate is less than 2%. Once the transmission curve measured, the optical parameters of the film can be obtained by calculation.

The interference mechanism of laser directional jamming to an infrared detection system was investigated in this study, and the chief jamming mode of the above-band laser was discussed. A pulsed-laser jamming experiment was conducted using the infrared detection system based on an indium antimonide (InSb) focal plane array(FPA) detector, and the response characteristics of the InSb FPA detector with above-band pulsed-laser jamming was analyzed. The failure mode and failure threshold of the InSb FPA detector were derived. The results provide a basis for further research into directional infrared countermeasure performance against infrared imaging guided weapons.

To determine the law of stress on the plastic shells of image intensifiers and to identify the characteristics of quality change, the deformation theory is used in this study to establish a mathematical model of silicone rubber deformation and to fit the stress curves of plastic shells. Accordingly, the inevitability and life-cycle characteristics of the plastic shells of image intensifiers are determined. The results show that the mathematical model is in good agreement with the experimental data and can characterize the stress conditions and life variations of plastic shells.

The glass fiber used in microchannel plate fabrication must be drawn in drawing furnaces. The temperature field distribution of the drawing furnace directly affects the uniformity of the wire diameter. Owing to the lack of theoretical research on glass fiber-drawing furnaces for microchannel plate fabrication, the designed drawing furnace and performance differences are based on experience. Based on the actual structure of a drawing furnace, this study aims to develop its corresponding 3D model on the basis of the theory of heat transfer analysis and to investigate the effects of the center of the furnace core, the uniformity of the heat insulation layer, and the drawing furnace temperature uniformity on the internal temperature field. Based on the theoretical analysis results, three suggestions are given to improve the drawing furnace for making micro channel plate.

In the application of ultrasonic infrared thermographic technology, it is usually necessary to extract features from infrared thermographic images based on artificial experience and then adopt a pattern recognition method to classify the cracks. The identification and positioning process of the cracks is complicated, and the recognition rate is low. Therefore, a method of crack detection and recognition in ultrasonic infrared thermal images based on convolutional neural network technology is proposed in this paper. Its feature is that the features can be directly learned from the ultrasonic infrared image to realize the classification of infrared thermal images containing cracks. Thesis through the research experiment of metal plate specimen of the crack in and do not contain infrared thermal images, the convolutional neural network model is established for whether the image contains crack classification, the results show that the parameter optimized convolution neural network model for ultrasonic infrared thermal images of crack classification accuracy rate reached 98.7%.

In this study, we consider the complex background and high interference that adversely affect infrared images of high-temperature pipelines in power plants and the requirements of image processing algorithms for inspection robot systems. We propose a high-temperature pipeline defect detection and extraction method based on an improved two-dimensional Otsu and region growth algorithms. After grayscale conversion, a 2D Otsu method was used to extract the pipeline area. Based on the grayscale histogram of the pipeline region and the average gray value of the neighborhood, automatic detection and positioning of multiple sub-points were realized. The segmentation of the defect area was accomplished using two methods. The adaptive threshold was determined based on the gray mean and standard deviation values of the growth area, while the growth criterion was improved using the gradient amplitude of the Prewitt operator. The experimental results show that the proposed algorithm can not only realize the automatic detection and positioning of various defects in high-temperature pipelines of power plants, but it additionally segments the defect regions more accurately with high accuracy and good real-time performance.

Owing to its scarce resources and excellent optical and physical properties, germanium is widely used in fiber-optic systems, infrared optical systems, electronic and solar energy applications, detectors, and other high-technology fields. It is an important functional and structural material which is needed in strategic industries. Two main methods of single crystal growth in germanium, Czochralski method(CZ)and vertical gradient freeze method(VGF), were briefly introduced. Technical parameters such as the method of germanium crystal growth, diameter and resistivity of germanium in popular germanium material-producing enterprises at home and abroad were analyzed and compared. Based on the properties of different single-crystal materials, the application fields and development status of germanium single crystals for infrared optics, germanium single crystal for solar cells, and high-purity germanium single crystal were analyzed.