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基于融合显著图和高效子窗口搜索的红外目标分割

刘松涛 刘振兴 姜宁

刘松涛, 刘振兴, 姜宁. 基于融合显著图和高效子窗口搜索的红外目标分割. 自动化学报, 2018, 44(12): 2210-2221. doi: 10.16383/j.aas.2018.c170142
引用本文: 刘松涛, 刘振兴, 姜宁. 基于融合显著图和高效子窗口搜索的红外目标分割. 自动化学报, 2018, 44(12): 2210-2221. doi: 10.16383/j.aas.2018.c170142
LIU Song-Tao, LIU Zhen-Xing, JIANG Ning. Target Segmentation of Infrared Image Using Fused Saliency Map and Efficient Subwindow Search. ACTA AUTOMATICA SINICA, 2018, 44(12): 2210-2221. doi: 10.16383/j.aas.2018.c170142
Citation: LIU Song-Tao, LIU Zhen-Xing, JIANG Ning. Target Segmentation of Infrared Image Using Fused Saliency Map and Efficient Subwindow Search. ACTA AUTOMATICA SINICA, 2018, 44(12): 2210-2221. doi: 10.16383/j.aas.2018.c170142

基于融合显著图和高效子窗口搜索的红外目标分割

doi: 10.16383/j.aas.2018.c170142
基金项目: 

中国博士后科学基金 2016T90979

中国博士后科学基金 2015M572694

国家自然科学基金 61303192

详细信息
    作者简介:

    刘振兴  海军大连舰艇学院信息系统系讲师.2002年、2007年和2010年获得海军大连舰艇学院学士、硕士和博士学位.主要研究方向为光电工程和电子对抗.E-mail:liuzhenxing@msn.com

    姜宁  海军大连舰艇学院信息系统系教授.1987年获得海军电子工程学院学士学位, 1996年和2000年获得大连理工大学硕士和博士学位, 南京理工大学博士后.主要研究方向为电子对抗和信息作战.E-mail:jiangning68@sohu.com

    通讯作者:

    刘松涛  海军大连舰艇学院信息系统系副教授.2000年、2003年和2006年获得海军航空工程学院学士、硕士和博士学位, 大连理工大学博士后.主要研究方向为图像处理, 光电工程和电子对抗, 本文通信作者.E-mail:navylst@163.com

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

Funds: 

China Postdoctoral Science Foundation 2016T90979

China Postdoctoral Science Foundation 2015M572694

National Natural Science Foundation of China 61303192

More Information
    Author Bio:

     Lecturer in the Department of Information System, Dalian Naval Academy. He received his bachelor degree, master degree and Ph. D. degree from Dalian Naval Academy in 2002, 2007 and 2010, respectively. His research interest covers optoelectronic engineering and electronic countermeasures

     Professor in the Department of Information System, Dalian Naval Academy. He received his bachelor degree from Naval Electronic Engineering Academy in 1987, and master degree and Ph. D. degree from Dalian University of Technology in 1996 and 2000, respectively, postdoctoral from Nanjing University of Technology. His research interest covers electronic countermeasure and information operation

    Corresponding author: LIU Song-Tao  Associate professor in the Department of Information System, Dalian Naval Academy. He received his bachelor degree, master degree and Ph. D. degree from Naval Aeronautical Engineering Institute, in 2000, 2003 and 2006, respectively, postdoctoral from Dalian University of Technology. His research interest covers image processing, optoelectronic engineering, and electronic countermeasures. Corresponding author of this paper
  • 摘要: 为了快速精确地分割红外图像目标,提出一种基于融合显著图和高效子窗口搜索的红外目标分割方法.在获取图像超像素的基础上,提取每个区域增强的Sigma特征,并考虑邻域对比度、背景对比度、空间距离和区域大小的影响,构建局部显著图,接着利用全局核密度估计构建全局显著图,然后融合局部和全局显著图实现图像显著性检测,最后应用高效子窗口搜索方法检测和筛选目标,实现红外目标分割.实验结果表明,新方法的显著图结果目标区域一致高亮且边缘清晰,背景杂波抑制效果好,可实现快速精确的目标分割.
    1)  本文责任编委 刘跃虎
  • 图  1  红外目标分割算法流程图

    Fig.  1  Flow chart of infrared target segmentation algorithm

    图  2  考虑不同影响因子的显著图效果

    Fig.  2  Saliency maps considering different impact factorss

    图  3  增强Sigma特征和灰度特征的显著图

    Fig.  3  Saliency map of enhanced Sigma feature and gray feature

    图  4  局部和全局显著图的重要性

    Fig.  4  The importance of local and global saliency map

    图  5  14种方法的显著图

    Fig.  5  Saliency maps of fourteen saliency detection methods

    图  6  14种方法的Pr和Roc曲线

    Fig.  6  Pr and Roc curves of fourteen saliency detection methods

    图  7  不同分割方法的分割结果

    Fig.  7  The segmentation results of different segmentation methods

    表  1  不同分割方法的分割精度和计算耗时

    Table  1  Segmentation precision and computational time of different segmentation methods

    新方法 文献[11] 文献[23] 文献[32] 文献[21] 文献[25]
    分割精度(F值) 0.7268 0.2288 0.5970 0.5709 0.1988 0.5536
    计算耗时(s) 0.65 0.31 6.7 4.29 2.6 0.13
    下载: 导出CSV
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  • 收稿日期:  2017-03-17
  • 录用日期:  2017-11-06
  • 刊出日期:  2018-12-20

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