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Proceedings Paper

Ship target segmentation and detection in complex optical remote sensing image based on component tree characteristics discrimination
Author(s): Wei Zhang; Chunjiang Bian; Xiao Zhao; Qingyu Hou
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Paper Abstract

Under the application background of sea-surface target surveillance based on optical remote sensing image, automatic sea-surface ship target recognition with complicated background is discussed in this paper. The technology this article focused on is divided into two parts, feature classification training and component class discrimination. In the feature classification training process, large numbers of sample images are used for feature selection and classifier determination of ship targets and false targets. Component tree characteristics discrimination achieves extraction of suspected target areas from complicated remote sensing image, and their features are entered to Fisher for ship target recognition. Experimental results show that the method discussed in this paper can deal with complex sea surface environment, and can avoid the interference of cloud cover, sea clutter and islands. The method can effectively achieve ship target recognition in complex sea background.

Paper Details

Date Published: 11 December 2012
PDF: 9 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 85582F (11 December 2012); doi: 10.1117/12.2000688
Show Author Affiliations
Wei Zhang, Harbin Institute of Technology (China)
Chunjiang Bian, Harbin Institute of Technology (China)
Ctr. for Space Science and Applied Research (China)
Xiao Zhao, Harbin Institute of Technology (China)
Qingyu Hou, Harbin Institute of Technology (China)


Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)

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