航空兵器

2019, v.26;No.314(06) 43-49

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Dim Moving Small Target Detection by Local and Global Variance Filtering on TemporalProfiles in Infrared Sequences
Dim Moving Small Target Detection by Local and Global Variance Filtering on Temporal Profiles in Infrared Sequences

Chen Hao;Liu Delian;

摘要(Abstract):

In this paper, the temporal different characteristics between the target and background pixels are used to detect dim moving targets in the slow-evolving complex background. A local and global variance filter on temporal profiles is presented that addresses the temporal characteristics of the target and background pixels to eliminate the large variation of background temporal profiles. Firstly, the temporal behaviors of different types of image pixels of practical infrared scenes are analyzed.Then, the new local and global variance filter is proposed. The baseline of the fluctuation level of background temporal profiles is obtained by using the local and global variance filter. The height of the target pulse signal is extracted by subtracting the baseline from the original temporal profiles. Finally, a new target detection criterion is designed. The proposed method is applied to detect dim and small targets in practical infrared sequence images. The experimental results show that the proposed algorithm has good detection performance for dim moving small targets in the complex background.

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基金项目(Foundation): National Natural Science Foundation of China(61774120)

作者(Author): Chen Hao;Liu Delian;

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