Infrared Small Target Detection Based on Flux Density and Direction Diversity in Gradient Vector Field

被引:76
作者
Liu, Depeng [1 ,2 ]
Cao, Lei [3 ,4 ]
Li, Zhengzhou [1 ,2 ,5 ]
Liu, Tianmei [1 ,2 ]
Che, Peng [1 ,2 ]
机构
[1] Chongqing Univ, Coll Commun Engn, Chongqing 400044, Peoples R China
[2] Chongqing Univ, Minist Educ, Key Lab Dependable Serv Comp Cyber Phys Soc, Chongqing 400044, Peoples R China
[3] Chinese Acad Sci, Inst Opt & Elect, Chengdu 610209, Sichuan, Peoples R China
[4] Chinese Acad Sci, Key Lab Beam Control, Chengdu 610209, Sichuan, Peoples R China
[5] Chinese Acad Sci, Inst Opt & Elect, Key Lab Beam Control, Chengdu 610209, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Flux density; gradient direction diversity (GDD); gradient vector field; infrared image; small target detection; FEATURES; CLUTTER; MINIMIZATION; BACKGROUNDS; FILTER; MODEL; IMAGE;
D O I
10.1109/JSTARS.2018.2828317
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The existing small target detection methods may suffer serious false alarm rate and low probability of detection in the situation of intricate background clutter. To cope with this problem, a novel small target detection method is proposed in this paper. Initially, the infrared image is transformed to the infrared gradient vector field (IGVF), where some new distinctive characters of the target and background clutter can be exploited. The small targets show as sink points, while the heavy clutter illustrates high direction coherence in IGVF. Then, the multiscale flux density (MFD) is proposed to quantify the extent of sink point character. In the MFD map, the small targets can be well enhanced and background clutters can be suppressed simultaneously. After that, by analyzing the coherence of heavy clutter shown in the IGVF, the gradient direction diversity (GDD) is presented. The residual noise caused by the heavy clutter in IGVF can be further suppressed by GDD. Finally, an adaptive threshold is adopted to separate the targets. Extensive experiments, including both real data and synthesized data, show that the proposed method outperforms other stateof-the-art methods, especially for infrared images with complex background clutter. Moreover, the experiments prove that the proposed method can work stably for different small target quantities, distances between adjacent targets, target shapes, and noise types with reasonable computational cost.
引用
收藏
页码:2528 / 2554
页数:27
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