In order to effectively enhance the low detection rates of dim and small targets caused by dynamic backgrounds, this paper proposes a detection algorithm for dim and small targets in sequence images based on spatiotemporal motion characteristics. With regard to the spatial domain, this paper proposes an improved anisotropic background filtering algorithm that makes full use of the gradient differences between the target and the background pixels in the eight directions of the spatial domain and selects the mean value of the three directions with the lowest diffusion function in the eight directions as the differential filter to obtain a differential image. Then, the paper proposes a directional energy correlation enhancement algorithm in the time domain. Finally, based on the above preprocessing operations, we construct a dim and small targets detection algorithm in sequence images with local motion characteristics, which achieves target detection by determining the number of occurrences of the target, the number of displacements, and the total cumulative area in these sequential images. Experiments show that the proposed detection algorithm in this paper can effectively improve the detection of dim and small targets in dynamic scenes.

中文翻译：

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基于时空运动特征的序列图像中弱小目标检测

为了有效地提高动态背景引起的弱小目标检测率，提出了一种基于时空运动特征的序列图像中弱小目标检测算法。关于空间域，本文提出了一种改进的各向异性背景滤波算法，该算法充分利用了目标像素与背景像素在空间域的八个方向上的梯度差，并选择了三个方向的平均值作为在八个方向上的最低扩散函数作为差分滤波器以获得差分图像。然后，提出了一种时域方向能量相关增强算法。最后，根据上述预处理操作，我们在具有局部运动特征的序列图像中构造了一个昏暗的小目标检测算法，该算法通过确定这些序列图像中目标的出现次数，位移数量和总累积面积来实现目标检测。实验表明，本文提出的检测算法可以有效地提高动态场景中暗弱目标的检测效率。