针对大多数CFAR 算法在检测舰船目标时受滑动窗口的限制,检测耗时长、效率低和易造成漏检等问题,提出一种将自适应窗口与CFAR 算法结合的舰船目标检测方法.首先利用目标的全局显著性找到其大致位置,根据目标区是否满足自适应窗口设置条件分别进行处理:采用剔除掉目标干扰的背景参数检测内部目标;采用检出目标与整体背景参数双重筛选边缘目标;最后将两部分合并进行后续处理.实验结果表明,本文方法能够准确快速地定位目标区域,且能精确检测并刻画目标形状,取得了较为满意的检测结果.

Most algorithms based on Constant False Alarm Rate (CFAR) which are used to detect ship targets often produce problems such as time waste,lower efficiency,missing detection and so on.To solve the problems caused by slipping windows,an algorithm based on CFAR and adaptive windows is proposed.Firstly,global saliency is measured to find the target potential regions.According to adaptive windows setting condition,target regions are divided into inside regions and edge regions: background parameters after getting rid of target pixels are used to detect inside regions;targets detected and global background parameters are united to detect edge regions.Final result is achieved by getting the two parts together to subsequent processing.The experiments show that the algorithm proposed in this paper can locate regions of targets fast and truly,depict the shape of the regions accurately and perform well for ship detection.