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复杂海况下遥感图像舰船目标检测方法研究

Ship Detection from Remote Sensing Image Under Complex Sea Conditions

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摘要

针对复杂海况下遥感图像舰船检测易受舰船尾迹、海杂波、油污和薄云等影响,导致检测结果可靠性较低且小目标舰船不易被检测的问题,提出一种自适应稳健背景的显著性优化舰船目标检测模型。利用顶帽算法对原图进行预处理,抑制舰船尾迹、海杂波等干扰;提出自适应超像素分割方法对稳健背景检测模型进行优化;改进基于均值信息的大津法(Otsu),确定舰船所在区域。结果表明,该方法可以在多种海况下有效检测舰船位置,具有较高的检测准确率(91.20%)、召回率(79.31%)及综合评价指标(84.00%),相比于其他显著性检测模型,该方法具有明显优势,适用于复杂海况下遥感图像小目标舰船检测。

Abstract

Under complex sea conditions, ship detection from remote sensing image is easily affected by the ship wake, sea clutter, oil, and thin cloud, which may lead to poor detection results and difficulty in the detection of small ships. Herein, we propose a saliency optimization ship target detection model based on an adaptive robust background. The proposed method uses the Tophat algorithm for preprocessing of the original image to suppress interference from the ship wake and sea clutter. Further, an adaptive superpixel segmentation method is proposed to optimize the robust background detection model. An improved Otsu segmentation method based on the mean information is proposed to determine the area where the ship is located. The experimental results demonstrate that the proposed method can effectively detect the location of a ship under various sea conditions. The proposed algorithm demonstrates high detection precision (91.20%), recall (79.31%), and comprehensive evaluation index (84.00%). When compared with the existing saliency detection algorithms in ship detection, the proposed algorithm exhibits obvious advantages; therefore, it is suitable for small ship detection based on the remote sensing images under complex sea conditions.

Newport宣传-MKS新实验室计划
补充资料

DOI:10.3788/LOP56.181007

所属栏目:图像处理

基金项目:中央高校青年教师科技创新项目;

收稿日期:2019-03-21

修改稿日期:2019-04-09

网络出版日期:2019-09-01

作者单位    点击查看

陈彦彤:大连海事大学信息科学技术学院, 辽宁 大连 116026
李雨阳:大连海事大学信息科学技术学院, 辽宁 大连 116026
姚婷婷:大连海事大学信息科学技术学院, 辽宁 大连 116026大连海事大学无人船协同创新研究院, 辽宁 大连 116026

联系人作者:陈彦彤(chenyantong1@yeah.net)

备注:中央高校青年教师科技创新项目;

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引用该论文

Yantong Chen,Yuyang Li,Tingting Yao. Ship Detection from Remote Sensing Image Under Complex Sea Conditions[J]. Laser & Optoelectronics Progress, 2019, 56(18): 181007

陈彦彤,李雨阳,姚婷婷. 复杂海况下遥感图像舰船目标检测方法研究[J]. 激光与光电子学进展, 2019, 56(18): 181007

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