基于海天线的舰船弱小目标检测 -- 西北工业大学学报,2019,37(1):35-40
论文:2019,Vol:37,Issue(1):35-40
引用本文:
胡耀辉, 张科, 邢超. 基于海天线的舰船弱小目标检测[J]. 西北工业大学学报
HU Yaohui, ZHANG Ke, XING Chao. Small and Dim Ship Target Detection Based on Sea-Sky-Line[J]. Northwestern polytechnical university

基于海天线的舰船弱小目标检测
胡耀辉, 张科, 邢超
西北工业大学 航天学院, 陕西 西安 710072
摘要:
针对复杂海天背景下,远距离成像的舰船弱小目标检测问题,提出一种基于海天线的检测方法。该方法首先采用基于全卷积网络的方法提取海天线,确定目标潜在区域,排除海天线区域外干扰,接着采用基于四向梯度的方法来检测舰船弱小目标。仿真结果表明:文中所提出的基于全卷积神经网络的海天线检测方法可以克服传统Otsu和行均值梯度法的缺点,在复杂海面背景中精确地检测出海天线;采用基于四向梯度的检测方法有效滤除了海面白色噪点,降低了虚警率,可以较好地实现舰船弱小目标的检测。
关键词:    海天线检测    全卷积神经网络    多向梯度    弱小目标检测   
Small and Dim Ship Target Detection Based on Sea-Sky-Line
HU Yaohui, ZHANG Ke, XING Chao
School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
In order to solve the problem of small and dim ship target detection under complex sea-sky background, we propose a target detection algorithm based on sea-sky line detection. Firstly, the paper locates the sea-sky-line based on fully convolutional networks, through which target potential area can be determined and disturbance can be excluded. Then the method based on the mean of four detection gradient is adopted to detect the small and dim ship target. The simulation results show that the method of sea-sky-line detection based on fully convolutional networks can overcome the disadvantages of the traditional methods and is suitable for complex background. The detection method proposed can filter the white noise point on the sea surface and thus can reduce false alarm,through which the detection of small and dim ship can be completed well.
Key words:    sea-sky-line detection    fully convolutional network    multi-gradient    small and dim target detection   
收稿日期: 2018-03-12     修回日期:
DOI: 10.1051/jnwpu/20193710035
通讯作者:     Email:
作者简介: 胡耀辉(1994-),西北工业大学硕士研究生,主要从事计算机视觉和深度学习研究。
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