Short-wave infrared imaging has the advantages of clear target detail expression, strong target identification ability, strong adaptability to haze climatic conditions and dust and smoke application environment, and can realize hidden imaging, low light level night vision detection, so more and more short-wave infrared imaging research is carried out. Based on the short wave infrared images as the goal, to carry out the short-wave infrared image colorization method based on color migration study, put forward an improved way of automatic unsupervised grayscale image coloring method, based on the depth of the convolutional neural network learning coloring method, and the global image of the transcendental and extracted from the whole image to calculate the local image features from image patches, The global prior provides image-level information, while the local feature represents the local texture or object at a given location. By combining these two features, the image is automatically colored to realize the color of short-wave infrared image, and the image quality evaluation after color is given. The experimental results show that the method has no loss of color image details, the image color information distribution is reasonable, high definition, obtained a new visual effect image, for target detection and recognition, key area monitoring to provide a more visual effect of target detection and recognition and scene monitoring means.
In this paper, a convenient, fast and efficient mid-wave infrared imaging spectrum acquisition system based on AOTF is designed and developed, which is used for target spectrum acquisition and image display. The experimental results show that the spectrometer can successfully acquire 3 μm to 5 μm mid-wave spectrum data, which lays a solid foundation for the acquisition, analysis and application of the target medium-wave spectrum data. This would provide system support for military reconnaissance, camouflage detection, stealth effect detection and evaluation, battlefield defense, etc.
In order to carry out the research on the spectrum characteristics and application of target in long-wave infrared band, this paper independently designed and developed a long-wave infrared imaging spectrum system based on filter and high-precision runner. This system is mainly composed of optical system, filter wheel, electronic system, structural system and control computer. After the target light passes through the front optical system, it is imaged on the primary image plane. A high-precision filter wheel is placed on the primary image plane. The wheel is used to switch the filters of different bands to achieve spectral acquisition. Finally, it is imaged on the focal plane of the long-wave infrared detector through the rear optical system. Among them, the optical system consists of two groups of coaxial spherical lens groups, namely, the front mirror group and the rear imaging mirror group. The structural system is the supporting structure of optical elements. The main function of the electronics system is to control the rotation of the runner and provide synchronous signals for the runner and the detector core. The functions of the electronic computer include data acquisition, image display, processing, work control, etc. According to the system indexes requirements, the optical system optical path design, distortion and MTF analysis are carried out in this paper. The electronic system synchronously controls the wheel for triggering and data acquisition. At the same time, the long-wave infrared spectral data processing software is developed to realize the reading, viewing and display of spectral image data and dynamic data viewing. Finally, the feasibility of the system function is verified by the spectral image data acquisition test of the designated scene and the UAV cooperation target. This system scheme would provide technical support for the spectral characteristics detection of military target in long-wave infrared band.
Under the condition of information war, combat equipment is faced with the serious threat of "discovery is destruction". In the all-weather and all-day reconnaissance environment, the infrared spectrum characteristics of the target and its effective control become the key to change detectability and improve survivability.In view of the important value of infrared spectrum characteristics in battle, this paper carries out data collection and comprehensive processing of MWIR spectrum in equipment testing. Firstly, combining with typical task process, a data collection method is established, which forms a theoretical analysis, atmospheric transmission, data collection, radiometric calibration model. Then, the radiation data processing research is carried out. Taking the digital image as the original data, the radiation emittance is obtained by radiation calibration. Based on the transmittance and radiation model, the calculation method of apparent temperature is established. To verify the method proposed in this paper, combined with helicopter infrared image data, the distribution of MWIR radiation field and temperature field of the equipment during takeoff, landing and dynamic flight is obtained, reaching 5% calibration measurement accuracy.The feasibility and validity of the method are verified.In this paper, the collection and processing of infrared spectrum characteristics is a useful exploration to improve the quality and efficiency of equipment inspection capability. It has practical value for improving equipment data and fully characterizing equipment capability in the actual environment.
Image quality is an important factor that influences the dynamic target information perception; it is the key factor of real-time target state analysis and judgment. In order to solve the multi-observation station comparison and video optimum seeking problem in the process of target information perception and recognition, an image quality assessment method based on visual characteristics is proposed for infrared target tracking. First, it analyses the basic infrared target image characteristics and application requirements, analyses the status and problems of the multi station optimum seeking technology. According to the expected research results, the processing flow of image processing is established. Then, the image quality objective assessment index is established, which reflects the basic characteristics of the target image, and the assessment index is integrated into the normalized assessment function. According to the quality assessment function, the infrared image quality assessment based on infrared target recognition and image analysis processing is realized, which is mainly characterized by the region of interest and dynamic visual characteristics. And on the basis of this technology, the real-time optimum seeking of multi station infrared target tracking image is completed. In order to verify the effectiveness of the method and the practical application effect, it designs the quality assessment and comparison of different station infrared images. Example shows that the method proposed in this paper can realize multi-observation station infrared image assessment comparison, image quality sorting, the optimum seeking of the infrared image based on the quality assessment. The results accord with the characteristics of infrared target image and dynamic visual characteristics.
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