Pulsed laser range-gated imaging system can reduce the influence of backscattered light in water. However, when searching for targets in unknown water, it is necessary to obtain the attenuation coefficient at the laser wavelength in the water. Usually, the attenuation coefficient of the water needs to be obtained by special instruments. In this paper, a numerical analysis method is proposed to extract the attenuation coefficient of water from the images collected by the range-gated imaging system. First, radiative transfer theory is used to model the imaging process of the pulsed laser range-gated imaging system. Then, the attenuation coefficient of the water is solved by numerical analysis method. At the same time, an experimental system is built to verify the method. The results under different water conditions show that, method in this paper is feasible and effective.
Infrared simulation software is widely used in the evaluation and model training of infrared equipment. Subject to foreign restrictions, domestic infrared simulation software hardly can meet the current requirements. However, visible simulation software is relatively mature. Thus, generated infrared images from visible images could be another way to replace infrared simulation software. In this paper, a deep learning style transfer method, cycle generative adversarial network, was introduced into the infrared simulation field. We captured visible and infrared images and extracted water surface targets to establish visible-infrared datasets. The cycle generative adversarial network model was applied to generate infrared simulation images from visible images. In terms of visual effect, generated infrared images were close to infrared images. To more holistically evaluate the visual quality of our results, we employ two tactics, structural similarity, and image quality. The result shows that the distribution of generated infrared images was well-matched to the origin visible images. And the image definition and details of generated infrared images were close to infrared images.
Calibration of the intrinsic parameters of a star sensor before and after its launch is essential. The existing techniques have not taken the centroiding error into consideration thoroughly. Meanwhile, the calibration operation is complex. Based on the principle of the SPGD algorithm, a calibration method fully considering the star image centroiding error is proposed in this work. Simulation result indicates that the intrinsic parameters are calibrated out and kept constantly after tens of iterations. The accuracy of principle point of the proposed SPGD based method is 4 times as the IAICM. As for the focus length, the accuracy is improved by 6 times compared to the IAICM. Simultaneously, the calibration operation becomes extremely simple
LLL (Low-light-level) / infrared image fusion can integrate both bands information of the target, it is beneficial for target detection and scene perception in the low visibility weather such as night, haze, rain, and snow. The quality of fused image is declined, when any channel image quality drops. There will be great changes in the brightness, contrast and noise on LLL images when environment illumination has obvious changes, but the current color fusion methods is not adapted to the environment illumination change in larger dynamic range. In this paper, LLL image characteristics are analyzed under different environment illumination, and a kind of adaptive color fusion method is proposed based on the RGB color space. The fused image can get better brightness and signal-to-noise ratio under the different intensity of illumination.
Low light level (LLL) imaging mainly relies on to detect weak night sky of targets reflecting, and environmental illumination is one of the important factors affecting the LLL image features. Germany's third-generation image intensifiers, Toshiba Terry company CS8620Ci types of CCD device as the main core to build LLL image acquisition experimental system, and LLL images are collected in a dark room with different illumination. This paper analyzes relationship between the statistical properties of the LLL image non-target area and environmental illumination, studies the laws between the mean, variance, autocorrelation, variance of sum and environmental illumination. And these laws based on experimental data were fitted to obtained specific mathematical expressions.
The low light level and infrared color fusion technology has achieved great success in the field of night vision, the technology is designed to make the hot target of fused image pop out with intenser colors, represent the background details with a nearest color appearance to nature, and improve the ability in target discovery, detection and identification. The low light level images have great noise under low illumination, and that the existing color fusion methods are easily to be influenced by low light level channel noise. To be explicit, when the low light level image noise is very large, the quality of the fused image decreases significantly, and even targets in infrared image would be submerged by the noise. This paper proposes an adaptive color night vision technology, the noise evaluation parameters of low light level image is introduced into fusion process, which improve the robustness of the color fusion. The color fuse results are still very good in low-light situations, which shows that this method can effectively improve the quality of low light level and infrared fused image under low illumination conditions.
The fusion of low light level and infrared images can synthesize the advantages of low light level imaging and infrared imaging, to make the details of the scene and targets richer. The quality of low light level and infrared images are the prerequisites to ensure the quality of fused image. The quality of low light level image is vulnerable to target contrast, light distribution and environmental illumination, especially under low illumination, low light level image noise significantly increased, image quality degradation, but the infrared image is not influenced by environmental illumination. In this paper, the influence of low light level image quality on low light level and infrared image fusion was analyzed from several aspects, such as target contrast, light distribution and ambient illumination, which can analysis the quality of low light level and infrared fused image.
Calculation to the transmission of infrared radiation is a key step in the research of the ability of detecting targets for an infrared detector system. Water vapor and carbon dioxide is the main factor causing the infrared radiation attenuation in the atmosphere. According to the existing experimental data, the effect of H2O and CO2 to the transmission of infrared radiation on horizontal route in the standard meteorological conditions is analyzed, and the transmittance in the different bants is simulated by establishing a reasonable mathematical model and using the method of curve fitting. The high-accuracy algorithm and it’s accuracy is put forward, and is compared with the traditional formula of the infrared radiation transmission. Research results of calculation to the transmission of infrared radiation can obtain higher calculation accuracy, and it is of great significance in the research of the ability of detecting targets for an infrared detector system which needs high-accuracy.
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