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首页> 外文会议>International symposium on photoelectronic detection and imaging;ISPDI 2011 >Research of real time dim target detection algorithm under occlusion in space background
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Research of real time dim target detection algorithm under occlusion in space background

机译：空间背景下遮挡的实时暗淡目标检测算法研究

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In this paper, a real time method for detecting multiple dim targets in deep space background is presented and special attention is paid to occlusion handling. We matched the stars in tow continuous images to get their speed at first and found moving target pairs through speed in both images, a kalman filter whose equation was updated by the centroid was adopted to track the target. The star's area was used to judge occlusion, a two Gaussian mixture model was build using the pixels' gray value of fusing region and we used the predicted value which the kalman filter given to detect the target. The model's parameters were estimated using the expectation-maximization method and applied to separate the target and the star as well as computing the precise centroid. Extensive experiments on real images sequences show that the proposed approach could effectively meet the requirements of the real-time detection with a low false alarm rate and a high detection probability, simulation results show that it can also create a accuracy centroid when occlusion happens.
机译：本文提出了一种在深空背景下检测多个暗目标的实时方法，并特别注意遮挡处理。我们将两幅连续图像中的星星进行匹配，以首先获得它们的速度，然后在两幅图像中找到通过速度移动的目标对，采用卡尔曼滤波器，其方程式由质心更新，以跟踪目标。使用恒星的面积判断遮挡，使用融合区域像素的灰度值建立两个高斯混合模型，并使用卡尔曼滤波器给出的预测值检测目标。使用期望最大化方法估计模型的参数，并将其用于分离目标和恒星以及计算精确质心。在真实图像序列上的大量实验表明，该方法可以有效地满足实时检测的要求，虚警率低，检测概率高，仿真结果表明该方法在遮挡发生时也可以产生准确的质心。

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