Study on Image Processing Technology in Imaging Laser Detection System

Zhong-liang Zhou, Jiaju Ying
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引用次数: 9

Abstract

With the extensive use of laser equipment and weapons systems, such as laser range finder and laser guided weapons, the energy of each laser source is greatly different. So the requirement of higher dynamic range is presented in the laser detection system. For the problem of insufficient dynamic range in Imaging Laser Detection System (ILDS), a method by image processing to extend the system dynamic range is discussed based on the existing hardware of wide-angle telecentric fish-eye lens and CMOS camera device Frame subtraction technique is commonly used in ILDS to recognize and locate the laser spot by filtering out background interference and noise. On this basis, it is proposed that in view of the receive laser energy's difference, uses the different method to expand the dynamic range. When the laser energy is low, the laser signal that may be submerged in noise can not be accurately interpreted and precisely localized. The technique of fuzzy weighted averaging filtering is used to get rid of noise and enhance detection sensitivity of the system, namely expansion detection lower limit. When the incident laser is strong, because the fish eye optical system would produce the reflection disturbance light, the imaging surface may be interfered by anomalous disturbance facula. Spot matching pattern recognition method is presented to remove the mixed light disturbance and enhance the recognition upper limit. The experimental results show that these methods can effectively improve the system's dynamic range and has a certain value of applied research
激光成像探测系统中图像处理技术的研究
随着激光设备和武器系统,如激光测距仪和激光制导武器的广泛使用,每个激光源的能量差别很大。因此对激光探测系统提出了更高的动态范围要求。针对成像激光探测系统(ILDS)动态范围不足的问题,基于现有的广角远心鱼眼镜头硬件和CMOS相机器件,讨论了一种通过图像处理来扩展系统动态范围的方法,在ILDS中常用的方法是通过滤除背景干扰和噪声来识别和定位激光光斑。在此基础上,提出针对接收激光能量的差异,采用不同的方法来扩大动态范围。当激光能量较低时,激光信号可能被淹没在噪声中,无法准确解释和精确定位。采用模糊加权平均滤波技术去除噪声,提高系统的检测灵敏度,即扩大检测下限。当入射激光较强时,由于鱼眼光学系统会产生反射扰动光,成像表面会受到异常扰动光斑的干扰。为了消除混合光干扰,提高识别上限,提出了斑点匹配模式识别方法。实验结果表明,这些方法能有效地提高系统的动态范围,具有一定的应用研究价值
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