Infrared Dim-Small Target Detection Based on Robust Principal Component Analysis and Multi-Point Constant False Alarm

doi:10.3788/AOS201939.0810001

CIOMP OpenIR

	Infrared Dim-Small Target Detection Based on Robust Principal Component Analysis and Multi-Point Constant False Alarm
	M.Ma; D.Wang; H.Sun; T.Zhang
	2019
发表期刊	Guangxue Xuebao/Acta Optica Sinica
ISSN	02532239
卷号	39 期号:8
摘要	To address the difficulty in detecting a dim-small target in single frame image caused by the complex background and polymorphism of the target, a method of rough extraction for threshold segmentation and precise detection for multi-point signal-to-noise ratio (SNR) is proposed. In the rough extraction stage, an improved threshold segmentation algorithm based on robust principal component analysis (RPCA) is proposed. The ratio of the mean value of the neighborhood sparseness to the mean value of the whole sparse image is used for the threshold segmentation, so as to further eliminate the isolated noise and the edge clutter of background cloud. In the precise detection stage, a multi-point constant false alarm detection algorithm based on statistical characteristics is proposed. The SNR of each pixel of candidate points in the neighborhood is obtained, and then the target point is extracted based on the false alarm rate threshold and statistical quantity threshold. The problem of polymorphic features caused by the dispersion of target energy will be overcome. Experimental results show that the detection probability of this algorithm reaches 95.6% under complex background, and the false alarm rate is 56.1% and 47.1% lower than that of single pixel and neighboring pixel based SNR computing methods, respectively. 2019, Chinese Lasers Press. All right reserved.
关键词	Signal to noise ratio,Alarm systems,Errors,Extraction,Image resolution,Image segmentation,Object recognition,Pixels,Principal component analysis
DOI	10.3788/AOS201939.0810001
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收录类别	EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/63145
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	M.Ma,D.Wang,H.Sun,et al. Infrared Dim-Small Target Detection Based on Robust Principal Component Analysis and Multi-Point Constant False Alarm[J]. Guangxue Xuebao/Acta Optica Sinica,2019,39(8).
APA	M.Ma,D.Wang,H.Sun,&T.Zhang.(2019).Infrared Dim-Small Target Detection Based on Robust Principal Component Analysis and Multi-Point Constant False Alarm.Guangxue Xuebao/Acta Optica Sinica,39(8).
MLA	M.Ma,et al."Infrared Dim-Small Target Detection Based on Robust Principal Component Analysis and Multi-Point Constant False Alarm".Guangxue Xuebao/Acta Optica Sinica 39.8(2019).

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