基于视觉感知机理的舰船目标检测

Ship Detection Based on Human Vision Perception

提出了一种基于视觉感知机理的光学遥感图像舰船目标检测的算法。该算法的核心思想在于设计并利用一组Gabor滤波器组来模拟人眼的视觉特性对基于可见光的遥感图像进行处理,从而达到对复杂海况背景抑制并对较暗舰船目标增强的目的。同时,该算法融合了海陆分割、云判处理等子模块,并充分考虑了人眼视觉的底层特性,从颜色、纹理、形态等各个角度进行疑似目标的筛选与剔除,得到最终的检测结果。实验结果显示,该算法具有较高的检测率和较强的鲁棒性,针对各类海况(包含暗舰船目标的情况)平均检测率达到85%以上,高于传统算法的51.3%。

A ship detection algorithm based on human vision perception is proposed. The key idea is using designed Gabor filters to simulate human vision perception for dealing with visible images, in order to reduce the negative influence of complex sea surface background and enhance the dark ship target. This algorithm includes several models to realize the separating of land and sea areas, the wiping of the cloud and the reduction of false alarms ratio using color, texture and morphologic characters. Experiment results show that the algorithm can effectively detect the ship targets in the complex sea environment, especially for dark ships, and the missed alarms ratio and false alarms ratio are very low, the ship target detection probability can be as high as 85%, higher than the 51.3% in traditional algorithm.