基于异常检测与双层筛选机制的SAR图像舰船检测方法  

A Method for Ship Detection in SAR Images Based on Anomaly Detection and Two-layer Censoring Mechanism

作　　者：翟亮[1] 李禹[1] 粟毅[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,长沙410073

出　　处：《计算机工程》2017年第4期244-250,共7页Computer Engineering

基　　金：国家自然科学基金(61171135)

摘　　要：针对现有合成孔径雷达(SAR)图像舰船目标智能检测算法中筛选误差较大的问题,提出一种新的SAR图像舰船目标检测方法。该方法将高光谱图像异常检测理论引入到SAR图像舰船目标检测处理中。通过图像转换将SAR图像转换成高光谱类型图像,采用异常检测算法实现舰船目标的检测预处理,得到感兴趣区域二值图。运用双层筛选机制,实现背景杂波的准确建模和舰船目标的快速检测。实验结果表明,该算法能够降低筛选误差,有效地消除虚假目标和旁瓣干扰,具有更好的结构保真度。Aiming at the problem of large censoring error of the existing intelligent detection aigorlmm ior stop talgct~ in SAR image, a novel method for ship detection based on Anomaly Detection（AD） and two-layer censoring algorithm is presented. The theory of anomaly detection of hyperspectral image is introduced into ship target detection in SAR imagery. The SAR image is transformed into the hyperspectral form by image conversion, and an anomaly detection is used algorithm to achieve the ship target detection preprocessing and the region of interest about ships. By two-layer censoring mechanism, accurate modeling of background clutter and ship target rapid detection are realized. Experimental results show that the algorithm can reduce the censoring error, and eliminate the number of false alarm and side-lobe effectively. Meanwhile, it can obtain higher fidelity of structure.

关 键 词：合成孔径雷达图像 舰船检测 异常检测 双层筛选 恒虚警率 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]