Ship detection in optical remote sensing image based on visual saliency and AdaBoost classifier

被引：0
作者：
王慧利 [1 ,2 ]
朱明 [1 ]
蔺春波 [1 ]
陈典兵 [1 ,2 ]
机构：
[1] Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences
[2] University of Chinese Academy of Sciences
来源：
Optoelectronics Letters | 2017年 / 13卷 / 02期
基金：
中国国家自然科学基金;
关键词：
HOG; In; Ship detection in optical remote sensing image based on visual saliency and AdaBoost classifier;
D O I：
暂无
中图分类号：
TP751 [图像处理方法];
学科分类号：
081002 ;
摘要：
In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient(S-HOG) feature, and the target can be recognized by Ada Boost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation.
引用
收藏
页码：151 / 155
页数：5
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