Single-Frame Infrared Small-Target Detection: A Survey

被引:170
作者
Zhao, Mingjing [1 ]
Li, Wei [2 ,3 ]
Li, Lu [4 ]
Hu, Jin [2 ,3 ]
Ma, Pengge [5 ]
Tao, Ran [2 ,3 ]
机构
[1] Beijing Inst Technol, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Sch Informat & Elect, Beijing 100081, Peoples R China
[3] Beijing Key Lab Fract Signals & Syst, Beijing 100081, Peoples R China
[4] Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100101, Peoples R China
[5] Zhengzhou Univ Aeronaut, Sch Intelligent Engn, Zhengzhou 450015, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
LOCAL CONTRAST METHOD; SPARSE-REPRESENTATION; ADAPTIVE DETECTION; LOW-RANK; IMAGE; ALGORITHM; ENTROPY; FILTER; DIM; KERNEL;
D O I
10.1109/MGRS.2022.3145502
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
Compared with radar and visible light imaging, infrared imaging has its own unique advantages, and in recent years, it has become a topic of intense research interest. Robust small-target detection is one of the key techniques in infrared search and tracking (IRST) applications, and there is no doubt that it has become an investigatory hot spot. In real applications, targets and backgrounds usually change quickly with very high velocities. In addition, a rapidly moving sensor platform typically makes the motion traces of the targets inconsistent. These factors reduce the detection performance of spatiotemporal-based methods, and thus single-frame infrared small-target detection is even more essential. In this survey, existing single-frame infrared small-target detection methods are comprehensively reviewed. © 2013 IEEE.
引用
收藏
页码:87 / 119
页数:33
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