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Automatic Detection of Small Moving Targets in a Five-ocular Composite Optical Imaging System

机译:五眼复合光学成像系统中小目标的自动检测

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It is quite difficult to realize the automatic detection and determination of the small moving targets by the images data captured from a mono-aperture imaging system. Therefore a five-ocular composite optical imaging system is designed. The system is constituted by an infrared imaging system in the center and four visible imaging subsystems around the center subsystem. According to the inner feature of the overlapping field of view in the five-ocular composite optical imaging system, the automatic detection and recognition algorithm of the small moving targets for this system is built up. The algorithm is divided into four steps: the first step is preprocessing to get rid of low frequency background pixels, the second step is detecting the candidates of the small moving targets in the high frequency images remained by preprocessing, the third step is determining the true small moving targets from the candidates, and the last step is combining the detecting results of the visible subsystems into the detecting results of the infrared subsystem to determine the small moving targets are "live" or "dead", because the "dead" targets with lower temperature are not observed in the infrared subsystem. The test result in the experimental system indicated that the designed detection and recognition algorithm increased the detecting probability of the small moving targets, and decreased the probability of false alarms. The detection and recognition method was proved to be feasible and effective.
机译:通过从单光圈成像系统捕获的图像数据来实现对小的运动目标的自动检测和确定是非常困难的。因此,设计了一种五眼复合光学成像系统。该系统由中心的红外成像系统和中心子系统周围的四个可见成像子系统组成。根据五眼复合光学成像系统中重叠视场的内在特征,建立了该系统小型运动目标的自动检测与识别算法。该算法分为四个步骤:第一步是进行预处理以去除低频背景像素,第二步是通过预处理检测残留在高频图像中的小运动目标的候选对象,第三步是确定真值。候选中的小移动目标,最后一步是将可见子系统的检测结果合并到红外子系统的检测结果中,确定小移动目标是“活动”还是“死亡”,因为“死”目标具有在红外子系统中未观察到较低的温度。实验系统的测试结果表明,所设计的检测识别算法提高了对小运动目标的检测概率,降低了虚警的概率。该检测和识别方法被证明是可行和有效的。

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