Infrared Technology
Junhong Su

Jan. 01, 1900
  • Vol. 42 Issue 4 1 (2020)
  • Yiqun ZHAO, Libin TANG, Yuping ZHANG, Rongbin JI, and Shengyi YANG

    The amorphous, .-GeTe, and .-GeTe phases of GeTe can be stably converted to each other under certain conditions. Because doping-based high-concentration holes can improve the thermoelectric and ferroelectric performances of GeTe, and it can be converted quickly between its amorphous and crystalline phases, GeTe has been applied to thermoelectric devices, spintronic devices, phase change switches, phase change memory, and others. Moreover, GeTe has a narrow optical band gap and high carrier mobility, which is expected to contribute positively to the development of high-performance infrared detectors. However, its application in the infrared detector field is still new. In this paper, its physical characteristics and its applications in areas including the thermoelectric, spintronic, and phase transition fields are reported. Based on its photoelectric properties, its application in the infrared detector field is expected.

    Jan. 01, 1900
  • Vol. 42 Issue 4 301 (2020)
  • Zhigang ZHAO, Xin WANG, Tinghai PENG, Canbing ZHAO, Likun XIA, and You ZHOU

    Depending on the capability of detecting scene radiance in both MWIR(middle wave infrared radiation) and LWIR(long wave infrared radiation) spectral bands, the dual-band IR(infrared radiation) technology ensures the use of two single-band sensors. Using the spectral advantages associated with the use of two single-band sensors, the dual-band IR technology can improve all-weather performance and the probability of mission success in almost all cases. Over the past 20 years, main occident have developed from dual-camera dual-band to single-camera dual-band infrared camera systems and equipped military, with higher resolution and greater range being the current requirements. At present, the dual-band IR technology mainly has three different applications. First, it improves the adaptability to different operational environments. Second, it improves the target detection and recognition probability of automatic systems. Third, through deep data processing, it is used to obtain more information about the target such as temperature and spectral feature, which helps prevent jammer and camouflage.

    Jan. 01, 1900
  • Vol. 42 Issue 4 312 (2020)
  • Zhen YANG, Xinmin GUO, Jianlong ZHANG, Xiangyan YU, and Quan ZHANG

    Near infrared Gaussian laser beams are crucial in many research studies, such as the interaction between intense laser and materials, laser cleaning, and laser combustion diagnostics. However, the non-uniformity of energy distribution of Gaussian beams hinders the further development of these fields. To improve cleaning efficiency and measuring accuracy, beam energy is typically expected to distribute uniformly within a larger working distance in practical applications. Nevertheless, the current beam shaping methods cannot satisfy requirements of long focal depth and high laser power tolerance simultaneously. Therefore, a novel optical system of Gaussian beam uniformization with long focal depth is proposed and designed based on the aberration effect of aspheric surface lens, which comprises an aspheric beam uniformization system and a spherical long focal collimation system. All lenses are fabricated with fused quartz and coated with antireflective film on the surface, which can achieve a 99.9% transmission efficiency in the optical system. The working wavelength of the system is 1064 nm, the working distance is 1000 mm, the total length of the system is 135.2 mm, and the laser power is higher than 300 W. The design results show that the effective focal depth of the shaped flat-topped Gaussian beam is ±100 mm, the uniformity of the beam is better than 95%, and the convergence angle is 17.52 mrad, which satisfy the requirements of the abovementioned application fields. Compared with other laser beam uniformization systems, the beam shaping system designed in this study possesses a simple structure and affords easy processing, low cost, long focal length, high laser power tolerance, and good beam uniformization.

    Jan. 01, 1900
  • Vol. 42 Issue 4 320 (2020)
  • Miao LI, Yuan HUANG, Yang SUN, and Zaiping LIN

    For space-based optical surveillance systems, estimated ballistic parameters are important output specifications based on limited boost-phase measures. They are useful for target classification and threat assessment. To improve estimation accuracy under a single satellite, passive ranging based on the atmospheric absorption of oxygen “A” band is introduced in this study. The performance of passive ranging under different atmosphere models, weather scenes, and signal-to-noise ratio are discussed and simulated separately in moderate resolution atmospheric transmission. Furthermore, the performance of ballistic estimation based on passive ranging is compared with an experiential method. Simulation results show that the proposed method can effectively improve the accuracy of ballistic estimation.

    Jan. 01, 1900
  • Vol. 42 Issue 4 328 (2020)
  • Yao WANG, and Xinyi TANG

    Based on the H.265/HEVC video coding standard, a hardware pipeline structure is implemented in this study in the regular mode of a binary arithmetic encoder in CABAC coding. Based on the characteristics of the algorithm, the hardware architecture of the coding engine is designed and optimized. The probability state data are stored in a SRAM, and the probability estimation updating operation is optimized using a lookup table. The coding data are packaged to simplify the calculation obtained by the update of the probability estimation to optimize the coding speed of the video data stream. Binary arithmetic coding uses a multistage pipeline structure to support four-way parallel encoding. Simulation results show that the hardware of the CABAC binary arithmetic coder can complete the encoding of four bins per clock cycle, which satisfies the higher frame rate of 1080p video real-time encoding requirements.

    Jan. 01, 1900
  • Vol. 42 Issue 4 335 (2020)
  • Li HE, Guo CHEN, Hong GUO, and Weiqi JIN

    High dynamic range imaging technology can reflect scene information comprehensively and effectively, which is beneficial for obtaining higher imaging qualities in high dynamic range scenes. However, the classic high dynamic range image fusion method of using a single camera through multiple-exposure fusion tends to result in the “ghost” problem in a dynamic scene, whereas the method of using multiple sensors in a simultaneous exposure system is complicated and expensive. Meanwhile, an extension method based on a single low dynamic range image loses details easily in underexposed or overexposed areas. These methods are often used under better lighting conditions. Hence, a high dynamic range image fusion method based on a dual-channel low-light-level (L3) CMOS camera is proposed for low illumination dynamic scenes. First, an image acquisition platform built using a dual-channel L3 CMOS camera is used to collect two images with different exposures for low illumination dynamic scenes. Based on the accumulative histogram, the principle of dynamic range extension is established, and the two images collected by the system are extended. Finally, the pixel level fusion method is used to fuse the sequence images after the dynamic range extension. The results show that the method of dynamic range extension fusion can yield high dynamic range images under L3 dynamic scenes as well as better imaging quality.

    Jan. 01, 1900
  • Vol. 42 Issue 4 340 (2020)
  • Lingzhi WANG, Zhenggang LEI, Hao ZHOU, Chunchao YU, Zhixiong YANG, Shaoli DUAN, and Dong NIE

    Hyper spectral image classification has become one of the most important research directions in detection technology; furthermore, it has been widely used in military and civilian fields. However, the significant number of bands, data redundancy, and low utilization of spatial features render the classification of hyper spectral images challenging, and most of existing hyper spectral image classifications use visible light or short-wave infrared data. Hence, a K-means classification method based on spectral and spatial features is proposed in this paper. First, spatial features are extracted; next, the spectral features are combined with the spatial features and the dimensions are reduced. Finally, the K-means algorithm is introduced to obtain classification results that are better than those of normal K-means, and the algorithm is applied to long-wave infrared hyper spectral image classification.

    Jan. 01, 1900
  • Vol. 42 Issue 4 348 (2020)
  • Shuguang WANG, Shengbin SHI, and Chunsheng HU

    To detect and track targets accurately when attacking small targets, while attempting to achieve a low signal-to-noise ratio and few pixels of small and dim targets in the air, images are preprocessed based on infrared video images using Gauss filtering and the top-hat operator in this study. The edge detection algorithm is used to detect and locate the target in the image. The initial position of the target is continuously tracked by the kernel correlation filter tracking algorithm. Finally, the tracking effect is quantitatively evaluated. Experimental results show that the tracking error of the maximum field of view angle does not exceed 0.0062., and that the average running speed can reach 25.3 fps/s. This method can effectively detect and track small and dim infrared targets in the air.

    Jan. 01, 1900
  • Vol. 42 Issue 4 356 (2020)
  • Yaling ZHANG, Linna JI, Fengbao YANG, and Xiaohui MU

    The distribution of difference feature frequency is crucial for establishing a multi-attribute fusion validity distribution synthesis of difference features of bimodal infrared images. To construct different feature frequency distributions of bimodal infrared images, a method of constructing a difference feature frequency distribution based on the K nearest neighbor(KNN) probability density estimation is proposed. The cumulative distribution function is used to obtain the true sequence value of the difference feature frequency; subsequently, the similarity measure of the statistically significant frequency sequence value and the real sequence value in the constructed frequency distribution of the difference feature are calculated. Experimental results show that non-parametric probability density estimation can be applied to the frequency distribution of difference features. The proposed method can accurately construct the frequency distribution of difference features compared with the MISE optimal bandwidth Gaussian kernel density estimation.

    Jan. 01, 1900
  • Vol. 42 Issue 4 361 (2020)
  • Chanfei LI, and Wenjing LIU

    To improve the fusion effect of infrared and visible light images, a novel fusion method is proposed. The visible light image is segmented into feature subimages with important scene information and grayscale scene subimages using a support vector machine and corrosion expansion algorithm based on the image block. The hot target edge of the infrared image is extracted and enhanced. Target, feature, and gray background subimages are obtained by combining the information of the former feature subimage with the maximum interclass variance method. Two feature subimages(grayscale scene and gray background) are fused by wavelet packet transform. During fusion, different fusion rules are implemented according to the characteristics of the subimages. Additionally, high frequency fusion coefficients are modified to render them more accurate and reliable. The infrared thermal target is injected into the previous fusion result to obtain the final fusion image. Experimental results show that the proposed algorithm is superior to other algorithms both in subjective and objective evaluations.

    Jan. 01, 1900
  • Vol. 42 Issue 4 370 (2020)
  • Gaixia CHAI, Quanmin GUO, and Xiaojuan SUN

    Owing to the problem that objective evaluation of fusion image quality is inconsistent with human visual effects in vehicle anti-halation, a new quality evaluation method is proposed in this paper for visible and infrared fusion images. The method can automatically determine halo critical gray values to divide fusion images into halo and no-halo regions by designing an adaptive iterative threshold algorithm. For the halo region, the halo limination effect is evaluated by designing a halo limination index. For the no-halo region, enhancement effects of color and detail information are evaluated from various aspects. Appropriate indexes are selected to constitute a complete image quality evaluation system. Fusion images of four different algorithms are evaluated to verify their rationality. Experimental analysis show that subjective and objective evaluation results of this method are consistent, rendering it suitable for evaluating anti-halation image quality and the algorithm of different visible and infrared fusion.

    Jan. 01, 1900
  • Vol. 42 Issue 4 378 (2020)
  • Ruhua CAI, Biao YANG, and Sunyong WU

    As single sensors cannot detect and track targets with low detection probability, a new multisensor box particle probability hypothesis density filter is proposed in this paper. The MS-BOX-PHD filter converts and fuses multiple sensor measurement sets into a new set, and the multitarget states are predicted and updated using a box particle probability hypothesis density filter. Numerical experiments show that the MS-BOX-PHD filter can estimate the state and number of multitargets when the target detection probability is low, unlike a single sensor box particle probability hypothesis density filter. Compared with the multisensor standard probability hypothesis density filter with interval measurement, the computational efficiency increased by 38.57% for the same tracking performance

    Jan. 01, 1900
  • Vol. 42 Issue 4 385 (2020)
  • Yi NIU, Lingtong GAN, and Yun MA

    The debonding of non-metallic materials can affect their performance, and infrared non- destructive testing can identify adhesive defects effectively. The boundary feature of adhesive defects is first investigated in this study based on infrared non-destructive testing; subsequently, a quantitative analysis method for identifying the boundary position of adhesive defects using the extreme value of a temperature gradient is obtained. Next, the Canny edge detection algorithm is used to identify the defect boundary of an adhesive defect model by numerical simulations and to identify experimental data simultaneously. For problems such as blurred boundaries and noise for recognition results, an improved algorithm for filtering out all “suspected boundaries” to preserve the “weak boundary” is proposed. The results show that the improved Canny algorithm can improve the integrity and accuracy of identifying adhesive defects from infrared non-destructive testing.

    Jan. 01, 1900
  • Vol. 42 Issue 4 393 (2020)
  • Xiangxin LI, Ni ZHANG, Ziheng HAO, Yufeng ZHU, and Dan LI

    The removal of a transition film from an ion-proof microchannel plate affects the performance and quality of the latter. In this paper, the removal technology of nitrocellulose transfer membrane is studied theoretically and experimentally. A nitrocellulose transition film was removed by hydrogen reduction heat treatment and ultraviolet irradiation. The surface composition and properties of the nitrocellulose were measured and analyzed by X-ray photoelectron spectroscopy, plate resistance, and current gain test. The removal of nitrocellulose and the performance of the microchannel are discussed. It is discovered that both hydrogen reduction heat treatment and ultraviolet irradiation can effectively remove the nitrocellulose membrane and sustain the stable performance of the microchannel plate.

    Jan. 01, 1900
  • Vol. 42 Issue 4 399 (2020)
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