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.

翻译：在红外图像序列中精确检测弱小运动目标是一项重大挑战。为解决这一问题，我们提出了一种名为时空局部特征差异（STLFD）结合自适应背景抑制（ABS）的新方法。该方法在空间域和时间域中利用滤波器，并对输出进行像素级自适应背景抑制，以增强目标与背景之间的对比度。所提出的方法包含三个步骤：首先，基于当前帧图像获取三个时域帧图像，并利用设计的空间域与时域滤波器提取两幅特征图；其次，融合空间域与时域信息生成时空特征图，并通过我们提出的像素级自适应背景抑制模块抑制噪声；最后，通过阈值分割得到二值图。实验结果表明，所提方法在红外弱小运动目标检测任务中优于现有最先进方法。