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Proceedings Paper

Graph Laplacian regularization based edge-preserving background estimation for single frame small target detection
Author(s): Kun Bai; Yuehuang Wang; Qiong Song; Mingna Liu; Jiandong Wu
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Paper Abstract

Small target detection in the clutter infrared image is a tough but significant work. In this paper, we will propose a novel small target detection method. First, Graph Laplacian regularization is utilized to model similarity feature of graph structure in the image. And Graph Laplacian regularization is incorporated in the background estimation model to preserve edges of background in single frame infrared image. At last, the edge-preserving estimated background is eliminated from original image to get foreground image which is used to detect the small target. Experimental results show that our proposed method can achieve edge-preserving estimation of background, suppress clutter efficiently, and get better detection results.

Paper Details

Date Published: 13 October 2015
PDF: 8 pages
Proc. SPIE 9648, Electro-Optical and Infrared Systems: Technology and Applications XII; and Quantum Information Science and Technology, 96480L (13 October 2015); doi: 10.1117/12.2193505
Show Author Affiliations
Kun Bai, Huazhong Univ. of Science and Technology (China)
National Key Lab. of Science and Technology on Multi-spectral Information Processing (China)
Yuehuang Wang, Huazhong Univ. of Science and Technology (China)
National Key Lab. of Science and Technology on Multi-spectral Information Processing (China)
Qiong Song, National Key Lab. of Science and Technology on Multi-spectral Information Processing (China)
Mingna Liu, Institute of Shanghai Aerospace Control Technology (China)
Jiandong Wu, Institute of Shanghai Aerospace Control Technology (China)


Published in SPIE Proceedings Vol. 9648:
Electro-Optical and Infrared Systems: Technology and Applications XII; and Quantum Information Science and Technology
David A. Huckridge; Mark T. Gruneisen; Miloslav Dusek; Reinhard Ebert; John G. Rarity, Editor(s)

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