海面舰船目标检测优化算法仿真

摘要

对于海面舰船目标图像受海空背景影响,容易在检测过程中出现外点和误检的问题,评测各类Harris角点检测改进方法,并结合极差方法,构建了一种协同多角度最优改进策略的特征点检测稳健算法.利用Harirs检测算法计算复杂度低的优势,分别从滤波器改进、自适应阈值、临近点剔除以及亚像素定位四个角度出发,筛选出每个角度下典型的优化方法,并在相同的试验条件下,分析对比各种优化方法的性能,从而得出最优的改进策略.基于极差的方法,可以对海空背景进行有效的剔除,最终给出了多角度下的协同优化算法.仿真结果表明,在同等试验条件下,上述算法的综合性能优于以往任一单角度的改进算法,可有效滤除海空背景杂波,检测出目标图像.%In the paper,we improve Harris comer detection algorithm with global optimization.After testing several modified Harris algorithms,a feature point corner detection algorithm of collaborating multi-angle optimal improvement strategies was constructed combining with the range method.From the views of filter modification,adaptive threshold,neighboring point excluding and sub-pixel positioning,we selected the typical optimal methods,then compared the results of these methods under the same test conditions and obtained the optimal modified strategies.To integrate these strategies can derive the multi-angle collaborative optimization algorithm.Numerical results show that the proposed algorithm is better than past modified ones.Filtering the sea and air clutter,images targets can be detected.