Target Segmentation of Infrared Image Using Fused Saliency Map and Efficient Subwindow Search

被引：0
作者：
Liu S.-T. [1 ]
Liu Z.-X. [1 ]
Jiang N. [1 ]
机构：
[1] Department of Information System, Dalian Naval Academy, Dalian
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2018年 / 44卷 / 12期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Efficient subwindow search; Global saliency map; Infrared image; Local saliency map; Region covariance;
D O I：
10.16383/j.aas.2018.c170142
中图分类号：
TB [一般工业技术];
学科分类号：
摘要：
In order to segment infrared target fast and precisely, a segmentation method using fused saliency map and efficient subwindow search is proposed. Firstly, based on image superpixels, the enhanced sigma feature of every region is extracted, and at the same time considering the influence of neighbor contrast, background contrast, spatial distance and region's size, the local saliency map is constructed. Next, the global saliency map is obtained by global kernel density estimation. Then, the saliency detection result of infrared image is obtained by fusing the local and global saliency maps. Finally, the efficient subwindow search method is used to detect and segment the target. Experimental results show that the saliency map of the proposed method has complete target feature, obvious edges and good background suppression, and that the algorithm can segment the infrared target fast and precisely. Copyright © 2018 Acta Automatica Sinica. All rights reserved.
引用
收藏
页码：2210 / 2221
页数：11
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