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中国科学院大学学报 ›› 2013, Vol. 30 ›› Issue (6): 793-799.DOI: 10.7523/j.issn.2095-6134.2013.06.012

• 信息与电子科学 • 上一篇    下一篇

ScanSAR图像舰船目标快速检测方法

林旭1, 洪峻2, 孙显1, 鄢懿3   

  1. 1. 中国科学院电子学研究所空间信息处理与应用系统技术重点实验室, 北京 100190;
    2. 中国科学院电子学研究所微波成像技术国家重点实验室, 北京 100190;
    3. 中国科学院大学电子电气与通信工程学院, 北京 100049
  • 收稿日期:2012-12-28 修回日期:2013-03-28 发布日期:2013-11-15
  • 通讯作者: 林旭
  • 基金资助:

    国家自然科学基金(41001285)资助

Fast ship detection method based on ScanSAR image

LIN Xu1, HONG Jun2, SUN Xian1, YAN Yi3   

  1. 1. Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    2. China National Key Laboratory of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
    3. School of Electronic Electrical and Communication engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2012-12-28 Revised:2013-03-28 Published:2013-11-15

摘要:

提出一种ScanSAR图像舰船目标快速检测方法.该方法通过周期性局部亮度变换技术降低了Scalloping效应对舰船检测的影响,在ScanSAR图像拼接前进行基于OpenMP的改进的双参数CFAR舰船目标检测,不仅避免了拼缝对舰船检测造成的巨大影响,而且极大地缩短了舰船检测的时间,提高了舰船检测的时效性,最后通过图像后处理从拼接后的ScanSAR图像中得到最终的检测结果.对15幅ScanSAR图像进行了实验,结果表明,该方法在提高检测性能的同时,检测的时效性也有明显改善.

关键词: ScanSAR 图像, Scalloping, 拼缝, OpenMP, 舰船快速检测

Abstract:

In this paper, a fast ship detection method based on ScanSAR image is presented. Firstly, the influence of scalloping noise on ship detection is reduced by seasonal local brightness transform. Secondly, an improved two-parameter CFAR ship detection based on OpenMP before ScanSAR images mosaicking is adopted, and it not only avoids the influence of splicing apertures on ship detection but also reduces the time of ship detection greatly. At last, the final detection targets are derived from mosaicking ScanSAR images. Experimental results on 15 different ScanSAR images show that the proposed system has good detection performance and prominent timeliness.

Key words: ScanSAR image, Scalloping, splicing aperture, OpenMP, ship fast detection

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