对复杂背景下暗弱点目标和背景杂波特性进行了分析,提出了一种基于全方位多尺度的形态学滤波和局部特征准则的点目标检测方法。实验结果表明,在复杂背景和低信噪比条件下,所提算法的目标检测概率达到99.8%,虚警率为0.1%。与最大中值滤波法、高斯差分尺度空间法、高斯混合模型法进行对比,结果表明,所提算法对复杂背景的抑制作用较好,且算法复杂度不高,易于实时实现。

The characteristics of dim point target and background clutter under a complex background are analyzed. A point target detection method based on the omnidirectional multiscale morphology filtering and local characteristic criterion is proposed. The experimental results show that, under the conditions of a complex background and a low signal-to-noise ratio, the detection probability of the proposed method reaches 99.8% with a false alarm probability of 0.1%. The results indicate that, when compared with the methods of Max-median filter, difference of Gaussian scale-space, and Gaussian mixture model, the proposed method possesses a better performance to suppress the complex background, and simultaneously a low complexity and an easy real-time implementation.