基于目标多特征的SAR影像舰船检测优化算法

doi:10.11896/jsjkx.200700180

计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 132-136.doi: 10.11896/jsjkx.200700180

• 图像处理&多媒体技术 • 上一篇下一篇

基于目标多特征的SAR影像舰船检测优化算法

颜军¹, 冯素云¹, 鹿琳琳², 王庆³, 蔡明祥¹

1 珠海欧比特宇航科技股份有限公司广东珠海519080
2 中国科学院空天信息创新研究院数字地球重点实验室北京100094
3 中国人民解放军93114部队北京100195

出版日期:2021-06-10 发布日期:2021-06-17
通讯作者: 鹿琳琳(lull@radi.ac.cn)
作者简介:2513414275@qq.com
基金资助:
广东省‘珠江人才计划'本土创新科研团队项目(2017BT01G115); 珠海市社会发展领域科技计划项目(ZH22036203200023PWC);中国科学院先导专项项目(XDA19090107);国家自然科学基金项目(41471369);国家重点研发计划项目(2017YFE0100800)

Optimization Algorithm of Ship Detection Based on Multi-feature in SAR Images

YAN Jun¹, FENG Su-yun¹, LU Lin-lin², WANG Qing³, CAI Ming-xiang¹

1 Zhuhai Orbita Aerospace Science Technology Co.,Ltd.,Zhuhai,Guangdong 519080,China
2 Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China
3 93114 Unit of the Chinese People's Liberation Army,Beijing 100195,China

Online:2021-06-10 Published:2021-06-17
Contact: YAN Jun,born in 1962,Ph.D.His main research interests include remote sen-sing technology and application and so on.
LU Lin-lin,born in 1984,Ph.D,asso-ciate professor.Her main research interests include urban remote sensing,remote sensing information extraction and classification.
Supported by:
Local Innovative and Research Teams Project of Guangdong Pearl River Talent Program(2017BT01G115),Zhuhai City Social Development Field Science and Technology Plan Project(ZH22036203200023PWC),Strategic Priority Research Program of Chinese Academy of Sciences (XDA19090107),National Natural Science Foundation of China (41471369) and National Key Research and Development Program(2017YFE0100800).

摘要/Abstract

摘要： 针对传统的舰船检测算法无法有效避免旁瓣效应对结果的影响,及多考虑舰船与背景之间的灰度对比度而未充分利用SAR影像上目标对象的几何特征造成检测精度较低的问题,提出了一种基于舰船多特征的目标检测算法。该方法利用方位角估算法与逐步逼近法剔除旁瓣效应对计算目标对象几何特征(面积、长宽比和矩形度)及灰度对比度特征的影响,利用变异系数法赋予4个特征不同的权重,计算出目标对象的置信度,选取最佳置信阈值,剔除非目标对象,优化检测结果。利用Sentinel-1影像数据对算法进行了验证,并将其与双参数CFAR算法和KSW双阈值算法进行了对比实验。实验结果表明:对于3张背景复杂度不同的影像,所提出的算法质量因子均超过了0.7且耗时最短,同时对于背景较为复杂的影像仍能保持较好的检测性能。

关键词: Sentinel-1, 方位角估计, 舰船检测, 权重分配, 最小外接矩形

Abstract: In view of that the traditional ship detection algorithms cannot effectively avoid the influence of the side lobe effect on results,which mostly consider the gray contrast between the ship and the background.The geometric characteristics of the target object on the SAR images are not fully utilized,and the detection accuracies are low,therefore a target detection algorithm based on the ship's multi-features is proposed.The azimuth estimation method and the stepwise approximation method are used to eliminate the influence of the side lobe effect on the geometric characteristics (area,aspect ratio and rectangularity) and gray contrast,and then the variance coefficient method is used to distribute different weight for the four features to calculate the confidence.By determining the best confidence threshold to remove the non-target objects among the candidate targets and optimize the detection results,this paper uses Sentinel-1 images to verify the algorithm,the two-parameter CFAR algorithm and the KSW double-threshold algorithm are used as comparative experiments.The experimental results show that for three images with different background complexities,the quality factor of the proposed algorithm exceeds 0.7 with the minimum calculation time,and it maintains optimal detection performance for images with complex background.

Key words: Azimuth estimation, Minimum bounding rectangle, Sentinel-1, Ship detection, Weight allocation

中图分类号:

TP753

颜军, 冯素云, 鹿琳琳, 王庆, 蔡明祥. 基于目标多特征的SAR影像舰船检测优化算法[J]. 计算机科学, 2021, 48(6A): 132-136. https://doi.org/10.11896/jsjkx.200700180

YAN Jun, FENG Su-yun, LU Lin-lin, WANG Qing, CAI Ming-xiang. Optimization Algorithm of Ship Detection Based on Multi-feature in SAR Images[J]. Computer Science, 2021, 48(6A): 132-136. https://doi.org/10.11896/jsjkx.200700180

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基于目标多特征的SAR影像舰船检测优化算法

Optimization Algorithm of Ship Detection Based on Multi-feature in SAR Images

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