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题名: Moving Point Target Detection Based on Higher Order Statistics in Very Low SNR
作者: Niu, Wenlong; Zheng, Wei; Yang, Zhen; Wu, Yong; Vagvolgyi, Balazs; Liu, Bo
作者部门: 空间技术部
通讯作者: Niu, WL (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing 100190, Peoples R China. ; Niu, WL (reprint author), Univ Chinese Acad Sci, Beijing 100039, Peoples R China.
关键词: Bispectrum estimation ; moving point target detection ; time series ; transient signal detection ; visual image sequence
刊名: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
ISSN号: 1545-598X
出版日期: 2018
卷号: 15, 期号:2, 页码:217-221
收录类别: SCI ; EI
项目资助者: Strategic Priority Program of Chinese Academy of Sciences [XDA04060300]
英文摘要: This letter presents an approach for the detection of moving point targets on high-frame-rate image sequences with low spatial resolution and low SNR based on higher order statistical theory. We propose a novel method for analyzing the time-domain evolution of image data for distinguishing between the background and the target in situations when the spatial signal of the target is swamped by noise. Our method is formulated to detect a time-domain transient signal of unknown scale and arrival time in noisy background. We proposed a bispectrum-based model to characterize the temporal behavior of pixels, and the detection ability under different frame rates and SNRs is analyzed. The method is evaluated using both simulated and real-world data, and we provide a comparison to other widely used point target detection approaches. Our experimental results demonstrate that our algorithm can efficiently detect extremely low SNR targets that are virtually invisible to humans based on time-domain analysis of image sequences.
语种: 英语
内容类型: 期刊论文
URI标识: http://ir.nssc.ac.cn/handle/122/6190
Appears in Collections:空间技术部_期刊论文

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