To overcome the interference of complex background and improve the detection ability of infrared small target under low signal-to-clutter ratio (SCR) scenes, a novel detection method based on gradient correlation measure (GCM) is proposed in this letter. Initially, the infrared gradient vector field (IGVF) of the original image is constructed based on the facet model. Then, a gradient correlation (GC) template is designed to distinguish the difference of local gradient between small targets and background. Finally, an adaptive threshold is adopted to extract small targets from background clutter. The proposed GCM method can identify the unique gradient characteristics of small targets. Experimental evaluations prove that the proposed method can achieve higher SCR scores in complex backgrounds. Especially in the scene where the gray contrast of small targets is low, the proposed GCM method shows a more robust detection performance.

中文翻译：

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基于梯度相关测度的红外小目标检测方法


为了克服复杂背景的干扰，提高低信杂比（SCR）场景下红外小目标的检测能力，提出了一种基于梯度相关测度（GCM）的新检测方法。首先，基于小面模型构建原始图像的红外梯度矢量场（IGVF）。然后，设计梯度相关（GC）模板来区分小目标和背景之间的局部梯度差异。最后，采用自适应阈值从背景杂波中提取小目标。所提出的GCM方法可以识别小目标独特的梯度特征。实验评估证明该方法可以在复杂背景下获得较高的SCR分数。特别是在小目标灰度对比度较低的场景中，所提出的GCM方法表现出更鲁棒的检测性能。