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.
程红, 刘思彤, 孙文邦, 杨帅. 基于分层特征描述的舰船目标鉴别[J]. 国土资源遥感, 2016, 28(2): 28-33.
CHENG Hong, LIU Sitong, SUN Wenbang, YANG Shuai. Ship target discrimination based on hierarchical feature description. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 28-33.
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