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遥感技术与应用
综述     
SAR图像船只分类识别研究进展
吴樊,王超,张波,张红,田小娟
(中国科学院遥感与数字地球研究所数字地球重点实验室,北京 100094)
Study on Vessel Classification in SAR Imagery:A Survey
Wu Fan,Wang Chao,Zhang Bo,Zhang Hong,Tian Xiaojuan
(Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China )
 全文: PDF(915 KB)  
摘要:

随着新一代SAR传感器的出现及应用,利用真实高分辨率、多极化SAR图像进行船只分类识别成为海上交通、渔业监测及国防应用的热点问题。首先回顾了SAR图像船只分类识别技术的发展。以近20 a国内外研究的重要成果为基础,对几何结构特征、散射特征和极化特征等船只分类特征进行了总结和比较,分析了其优缺点;总结了各种SAR图像船只分类识别算法的技术特点,并分析了各方法的适用性。最后对SAR图像船只分类识别技术的应用前景和发展趋势进行了阐述。

关键词: 合成孔径雷达船只分类识别    
Abstract:

With the technical promotion of Synthetic Aperture Radar (SAR),the study on vessel detection and classification using current new generation (high resolution and multi-polarization)SAR image has become a hot research topic for maritime traffic monitoring,fishery control and other applications.Techniques of vessel classification with SAR image are reviewed in this paper.Based on the researches in recent twenty years,image features (including geometric features,backscattering features and polarimetric features)for vessel classification are summarized;furthermore,merits and demerits of them are pointed out.The Vessel classification algorithms with SAR image are also investigated and summarized.Finally,some comments and suggestions are given for the development of vessel classification application.

Key words: Synthetic Aperture Radar (SAR)    Vessel    Classification
收稿日期: 2012-10-30 出版日期: 2014-05-14
:  TP 79  
基金资助:

国家自然科学基金项目“高分辨率SAR图像船只特征分析与分类方法研究”(40871191),国家863计划项目“基于多源SAR影像的船只检测与分类研究”(2009AA12Z139)。

作者简介: 吴樊(1976-),男,湖南醴陵人,副研究员,博士,主要从事SAR图像信息提取和目标检测识别研究。Email:fwu@ceode.ac.cn。
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引用本文:

吴樊,王超,张波,张红,田小娟. SAR图像船只分类识别研究进展[J]. 遥感技术与应用, 10.11873/j.issn.1004\|0323.2014.1.0001.

Wu Fan,Wang Chao,Zhang Bo,Zhang Hong,Tian Xiaojuan. Study on Vessel Classification in SAR Imagery:A Survey. Remote Sensing Technology and Application, 10.11873/j.issn.1004\|0323.2014.1.0001.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004\|0323.2014.1.0001        http://www.rsta.ac.cn/CN/Y2014/V29/I1/1

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