Detecting small moving targets accurately in infrared (IR) image sequences is a significant challenge. To address this problem, we propose a novel method called spatial-temporal local feature difference (STLFD) with adaptive background suppression (ABS). Our approach utilizes filters in the spatial and temporal domains and performs pixel-level ABS on the output to enhance the contrast between the target and the background. The proposed method comprises three steps. First, we obtain three temporal frame images based on the current frame image and extract two feature maps using the designed spatial domain and temporal domain filters. Next, we fuse the information of the spatial domain and temporal domain to produce the spatial-temporal feature maps and suppress noise using our pixel-level ABS module. Finally, we obtain the segmented binary map by applying a threshold. Our experimental results demonstrate that the proposed method outperforms existing state-of-the-art methods for infrared small-moving target detection.

通过使用空时局部特征差异（STLFD）与自适应背景抑制（ABS）的方法，我们提出了一种有效准确地检测红外（IR）图像序列中小目标的新方法。该方法利用了空间和时间域中的滤波器，并在输出上进行像素级背景抑制，以增强目标和背景之间的对比度。我们的实验结果表明，该方法在红外小目标检测方面优于现有的最先进方法。

一种自适应的时空局部特征差异方法用于红外小移动目标检测