| Technology and Methodology |
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Ship target discrimination based on hierarchical feature description |
| CHENG Hong1, LIU Sitong1,2, SUN Wenbang1, YANG Shuai1 |
1. Aviation University of Air Force, Changchun 130022, China;
2. Xi'an Flight Academy of Air Force, Xi'an 710306, China |
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Abstract In view of the problem that current methods cannot reach a good balance between capability of discrimination, utility and computational complexity, the authors have proposed in this paper an algorithm based on hierarchical feature description. Firstly, simple shape or geometrical features are extracted to get rid of large numbers of false-alarm targets based on weighted voting. Secondly, complex discrimination features are selected to form the optimal feature set by feature separation. And then the feature set is used to support vector machine to get the real ship target. Experimental results show that the proposed algorithm in this paper, which extracts hierarchical features to certain regions identified, can effectively eliminate false alarms, reduce the amount of computation, and improve accuracy and efficiency of discrimination, and can also reduce the influence of external factors, remove false alarm and reserve the targets effectively, with time spending being only 1/3 of the common method.
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| Keywords
high resolution remote sensing
fault
vectorization
fault attitude measurement
Google Earth Plug-in
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Issue Date: 14 April 2016
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2016,
Vol. 28
