杂乱
计算机科学
人工智能
度量(数据仓库)
相关性
对比度(视觉)
模式识别(心理学)
红外线的
干扰(通信)
计算机视觉
数学
雷达
物理
光学
电信
计算机网络
频道(广播)
几何学
数据库
作者
Xiangyue Zhang,Jingyu Ru,Chengdong Wu
标识
DOI:10.1109/lgrs.2022.3201280
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 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI