用梯度LOG算子实现小目标实时跟踪

A New Small Target Tracking Method Based on the Gradient LOG Operator

为提高复杂背景条件下小目标检测及跟踪的稳定性,提出了一种基于梯度LOG算子的光团目标检测跟踪算法。首先建立了梯度图像中小目标的成像模型,能够较好地适应背景光照变化。然后根据尺度空间的基本理论构造了一种针对该成像模型的目标检测算子,分析并证明了该算子具有尺度不变性的优点,设计并实现了基于梯度LOG算子的小目标跟踪方案,实验结果表明:梯度LOG算子能够较好地跟踪复杂背景中的光团目标,定位精度可达亚像素级,且具有计算量小,抗噪声能力强等优点。

To improve the stability and accuracy of small target tracking in cluttering background, a new small target tracking method based on gradient Laplacian of Gaussian （LOG） operator was proposed. First, imaging model of small target in gradient image was presented. Second, the theory of scale space was used to design a new operator for target detection and tracking. Then, the property of scale invariant was analyzed and proved, and a tracking scheme based on the gradient LOG operator was proposed. Experimental results show that the gradient LOG operator is appropriate to describe small target in complex background, and the detection precision is in the level of sub-pixel. Furthermore, it is efficient and robust to noise.