一种高分辨率遥感图像舰船检测方法研究

A ship detection method with high-resolution remote sensing images

本文针对传统舰船检测方法在复杂海况条件下检测结果不佳,易造成大量虚警的问题,提出了在利用自适应分割算法进行舰船快速筛选的基础上采用方向梯度直方图(HOG)特征提取舰船的边缘结构信息,通过监督学习进行舰船检测虚警滤除的新算法。与现有算法相比,这种算法克服了由云、浪造成的舰船目标虚警滤除问题,在保证鲁棒性的同时兼顾了算法效率,并使用该方法对遥感图像进行了检测试验。

This paper proposed a method for automatic ship targets detection in remote sensing images. The method uses adaptive segmentation algorithm for getting possible ship targets first, and then calculates Histograms of Oriented Gradient （HOG） feature to ex- tract the structural information of ships, followed by supervised learning algorithm to identify the possible ship targets. Multi-scale slid- ing-window is used to handle targets with different scales. The experimental results proved that this method could have a good precision and robustness with high efficiency.