提出一种基于显著性的高海况SAR图像船舶目标检测方法Itti-SAR，该方法由显著图提取与连接性判断两个阶段组成。在显著图提取阶段，针对SAR图像特性，将改进的方向特征和一致性特征引入传统视觉注意模型，以构建适用于SAR图像的显著性模型，实现高海况SAR图像船舶目标显著图的提取。在连接性判断阶段，采用密度约束对显著区域的连接性进行判断，防止将单个目标检测为多个，从而进一步降低虚警。在多幅SAR图像上的实验结果验证该方法的有效性，与经典CFAR算法的对比实验显示出其查准率、召回率高和不依赖于先验知识的优点。
In this study, a ship target detection method in high sea state SAR image, named Itti-SAR, based on saliency is proposed, which consists of two stages:saliency image extraction and connectivity judgment. In the stage of saliency map extraction, taking the characteristics of SAR images into consideration, the improved direction feature and consistency feature are introduced into the traditional visual attention model to construct a saliency model suitable for SAR images, which realizes the extraction of ship target saliency maps for high sea state SAR images. In the stage of connectivity judgment, the density constraint is used to judge the connectivity of salient areas to prevent the detection of a single target into multiple, thereby further reducing false alarms. The experimental results on several SAR images verify the effectiveness of the method. The experimental results show that compared with the classical CFAR algorithm, the proposed method has the advantages of high precision, high recall rate and independent of prior knowledge.
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