基于多特征加权的SAR影像舰船检测优化方法

赵泉华; 王肖; 李玉; 王光辉

doi:10.11959/j.issn.1000-436x.2020013

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基于多特征加权的SAR影像舰船检测优化方法

学术论文 | 更新时间：2024-06-05

- 基于多特征加权的SAR影像舰船检测优化方法
- Ship detection optimization method in SAR imagery based on multi-feature weighting
- 通信学报 2020年41卷第3期页码：91-101
- 作者机构：
  
  1. 辽宁工程技术大学测绘与地理科学学院，辽宁阜新 123000
  2. 国家测绘地理信息局卫星测绘应用中心，北京 100048
- 作者简介：
  
  [ "赵泉华（1978- ），女，河北承德人，博士，辽宁工程技术大学教授、博士生导师，主要研究方向为随机几何、空间统计学、模糊集理论等在遥感图像建模、解译及海洋环境遥感中的应用" ]
  [ "王肖（1996- ），女，辽宁阜新人，辽宁工程技术大学硕士生，主要研究方向为遥感图像处理" ]
  [ "李玉（1963- ），男，吉林长春人，博士，辽宁工程技术大学教授、博士生导师，主要研究方向为遥感图像处理" ]
  [ "王光辉（1982- ），男，河南商丘人，国家测绘地理信息局高级工程师，主要研究方向为遥感图像处理" ]
- 基金信息：
  
  辽宁省教育厅科学技术研究基金资助项目(LJ2019JL001)
- DOI：10.11959/j.issn.1000-436x.2020013
  中图分类号： TP237
- 网络出版日期：2020-03，
  
  纸质出版日期：2020-03-25
- 稿件说明：
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赵泉华, 王肖, 李玉, 等. 基于多特征加权的SAR影像舰船检测优化方法[J]. 通信学报, 2020,41(3):91-101.

Quanhua ZHAO, Xiao WANG, Yu LI, et al. Ship detection optimization method in SAR imagery based on multi-feature weighting[J]. Journal on communications, 2020, 41(3): 91-101.
赵泉华, 王肖, 李玉, 等. 基于多特征加权的SAR影像舰船检测优化方法[J]. 通信学报, 2020,41(3):91-101. DOI： 10.11959/j.issn.1000-436x.2020013.

Quanhua ZHAO, Xiao WANG, Yu LI, et al. Ship detection optimization method in SAR imagery based on multi-feature weighting[J]. Journal on communications, 2020, 41(3): 91-101. DOI： 10.11959/j.issn.1000-436x.2020013.

摘要

针对虚警目标较多的复杂场景中，传统舰船检测算法检测结果精度偏低的问题，提出了一种基于多特征加权的SAR影像舰船检测优化方法。首先，采用标记分水岭算法对SAR幅度影像进行去陆操作；其次，利用基于对数正态分布的恒虚警率算法，得到去陆 SAR 影像的候选目标；再次，提取候选目标的长宽比、舰船面积和对比度3个特征；最后，提出变异系数法对3个特征进行权重分配，并结合候选目标的归一化特征矢量计算其特征置信度，再确定最佳置信度，去除候选目标中的虚警目标，优化舰船检测结果。为了验证所提方法，选取不同复杂场景的高分三号SAR影像进行舰船检测实验。实验结果表明，所提方法具有可行性和有效性。

Abstract

Aiming at the problem that the accuracy of traditional ship detection algorithms is not satisfying in complex scene with many false alarm targets

a ship detection optimization method in SAR imagery based on multi-feature weighting was proposed.Firstly

the marker-based watershed algorithm was employed to remove land from SAR amplitude image.Then

the CFAR algorithm based on log-normal distribution was used to obtain candidate targets from no land image.Furthermore

the length to width ratio

the ship area and the contrast ratio of the candidate targets were extracted.Finally

a variance coefficient method was proposed to distribute the weight of the three features

and the confidence levels were calculated by combining the normalized feature vectors of the candidate targets with the feature weight.By determining the best confidence level

false alarm targets among the candidate targets were removed to optimize ship detection results.In order to verify the proposed method

experiments were carried on with the GF-3 SAR images of different complex scenes.The experimental results show that the proposed method is feasible and effective.

关键词

Keywords

references

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