An Infrared Small Target Detection Method Based on Gradient Correlation Measure

被引:3
作者
Zhang, Xiangyue [1 ]
Ru, Jingyu [1 ]
Wu, Chengdong [1 ]
机构
[1] Northeastern Univ, Fac Robot Sci & Engn, Shenyang 110819, Peoples R China
关键词
Correlation; Object detection; Clutter; Estimation; Image edge detection; Geoscience and remote sensing; Filtering; Gradient correlation measure (GCM); gradient field; gradient template; infrared small target detection; ALGORITHM;
D O I
10.1109/LGRS.2022.3201280
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
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.
引用
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页数:5
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