基于S-HOG的遥感图像舰船目标检测

Ship Target Detection in Remote Sensing Image Based on S-HOG

随着高分辨率卫星遥感成像技术的不断发展,可见光遥感图像舰船目标检测成为热门课题,其在军舰探测、精确制导等军用领域以及海面搜救、渔船监测等民用领域具有极其重要的战略意义。针对遥感图像中的舰船检测易受云雾、波浪、岛屿等因素干扰导致虚警率高的问题,提出了基于舰船方向梯度直方图(Ship Histagram of Oriented Gradient,S-HOG)特征的舰船鉴别算法。首先利用异常点检测提取目标候选区域得到可疑目标切片,然后统计其S-HOG特征剔除虚警,从而有效提取真正的舰船目标。实验结果表明,所提算法能在保证高检测率的同时显著降低虚警率,抗干扰能力强,鲁棒性高。

With the continuous development of high-resolution satellite remote sensing imaging technology,ship target detection based on visible remote sensing image has become a hot topic,which is of great strategic significance in military fields such as warship detection,precise guidance,and civilian fields such as sea search and rescue,fishing vessel monitoring,etc.Aiming at the problem that ship detection in remote sensing image is easy to be interfered by cloud,wave,island and other factors,which leads to high false alarm rate,a ship identification algorithm based on the characteristics of ship histogram of oriented gradient(S-HOG)is proposed.Firstly,the candidate region of the target is extracted by abnormal point detection to get the suspicious target slice,and then the S-HOG feature is counted to eliminate the false alarm,so as to effectively extract the real ship target.Experimental results show that the algorithm can significantly reduce the false alarm rate while ensuring high detection rate,and has strong anti-interference ability and high robustness.