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Proceedings Paper

The maritime infrared target detection based on mixture Gaussian background modeling in the Fourier domain
Author(s): Anran Zhou; Weixin Xie; Jihong Pei
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Paper Abstract

The sea background often fluctuates violently and has a low contrast with the target, which brings difficulties in detecting the infrared maritime targets. To solve this problem, the mixture Gaussian background modeling for sea background in the Fourier domain (FGMM) was proposed. First, the mixture Gaussian background model was constructed for the amplitude spectrum sequence at each frequency point. Second, the amplitude spectrum of the test frame was compared with the mixture Gaussian background model to separate the background and foreground frequency points. And the parameters of each Gaussian distribution were updated to adapt to the change of seawater. Also, the two features of the neighborhood amplitude spectrum contrast and the information entropy of local amplitude spectrum were fused into the mixture Gaussian background model to get the final detection results. Experimental results showed that the proposed method has good effects in suppressing the seawater and detecting the targets. Moreover, compared with the traditional spatial mixture Gaussian background modeling algorithm, its performance has been significantly improved.

Paper Details

Date Published: 14 February 2020
PDF: 9 pages
Proc. SPIE 11429, MIPPR 2019: Automatic Target Recognition and Navigation, 1142903 (14 February 2020); doi: 10.1117/12.2535703
Show Author Affiliations
Anran Zhou, ShenZhen Univ. (China)
Weixin Xie, ShenZhen Univ. (China)
Jihong Pei, ShenZhen Univ. (China)


Published in SPIE Proceedings Vol. 11429:
MIPPR 2019: Automatic Target Recognition and Navigation
Jianguo Liu; Hanyu Hong; Xia Hua, Editor(s)

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