CIOMP OpenIR  > 中科院长春光机所知识产出
Moving target detection under moving base
Lu, M.; Y. Gao and M. Zhu
2016
发表期刊Guangxue Jingmi Gongcheng/Optics and Precision Engineering
卷号24期号:7
摘要A detection algorithm, based on the combined local-global (CLG) optical-flow model and Gaussian pyramid for a moving target appearing against a dynamic background, can compensate for the inadaptability of the classic Horn-Schunck algorithm to illumination changes and reduce the number of needed calculations. Incorporating the hypothesis of gradient conservation into the traditional CLG optical-flow model and combining structure and texture decomposition enable this algorithm to minimize the impact of illumination changes on optical-flow estimates. Further, calculating optical-flow with the Gaussian pyramid by layers and computing optical-flow at other points using an optical-flow iterative with higher gray-level points together reduce the number of calculations required to improve detection efficiency. Finally, this proposed method achieves the detection of a moving target against a dynamic background, according to the background motion vector determined by the displacement and magnitude of the optical-flow. Simulation results indicate that this algorithm, in comparison to the traditional Horn-Schunck optical-flow algorithm, accurately detects a moving target undergoing illumination changes against a dynamic background and simultaneously demonstrates a significant reduction in the number of computations needed to improve detection efficiency.
文章类型期刊
收录类别EI
语种中文
文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/57112
专题中科院长春光机所知识产出
推荐引用方式
GB/T 7714
Lu, M.,Y. Gao and M. Zhu. Moving target detection under moving base[J]. Guangxue Jingmi Gongcheng/Optics and Precision Engineering,2016,24(7).
APA Lu, M.,&Y. Gao and M. Zhu.(2016).Moving target detection under moving base.Guangxue Jingmi Gongcheng/Optics and Precision Engineering,24(7).
MLA Lu, M.,et al."Moving target detection under moving base".Guangxue Jingmi Gongcheng/Optics and Precision Engineering 24.7(2016).
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