图象序列中检测运动小目标的递归算法

Recursive Algorithm for the Detection of Small Moving Target in Image Sequence

分析了一种基于卡尔曼滤波理论的时域递归低通滤波算法。这种算法根据运动小目标 ,背景干扰和噪声在图象序列中的差异 ,能够抑制背景 ,增强小目标并将其从相对静止的背景中有效地分离出来。在恒虚警概率条件下 ,该算法可以在低信噪比的情况下 ,减小背景干扰和随机噪声的影响 ,提高信噪比。选取适当的阈值 ,能够得到清晰的小目标轮廓。通过仿真 ,验证了这种算法的有效性。

A time domain recursive low pass filtering algorithm based on Kalman filtering theory is analyzed.The algorithm can effectively separated the small moving target from the relatively stationary backgrond according to the differences among the small moving target,background interference and noise by inhibiting the background and enhancing the target.With the conditions of constant false alarm probability and low signal to noise ratio,the signal to noise ratio can be improved by reducing the effects of background interference and random noise.A clear profile of small moving target can be obtained through selecting a suitable threshold.The effectiveness of this algorithm is demonstrated by simulation.