摘要
CFAR(Constant False Alarm Rate,恒虚警)是红外弱小目标检测系统中的一项核心技术,为了克服传统单帧探测方法在复杂背景下的不足,本文提出了一种基于威布尔分布的阈值更新OSTWO CFAR检测方法。对红外图像进行Laplace滤波和杂波拟合后,设计CFAR检测器,图像中的每个检测单元,根据周围单元来确定其阈值,再判定其为目标还是背景杂波。试验表明,提出的算法能够控制虚警率和提高探测率,并且很好的解决了复杂背景下目标遮挡和背景变化的问题。
CFAR （Constant False Alarm Rate） is a key technology in infrared small target detection system. In order to overcome the shortcomings of the method of the single image detection under complex background, a proposal for threshold updating OSTWO CFAR detection based on Weibull distribution was presented. Infrared image was filtered by the Laplace filter and modeled, after that, CFAR detector was designed. For every test unit, threshold was calculated by the units around it, and then it was judged to be a target or backgiound clutter. The experiment demonstrates that our algorithm can control false alarm rate effectively while improving detection rate, and solve the problems when the target is in the complex background with covering and changing background.
出处
《红外技术》
CSCD
北大核心
2011年第10期559-563,共5页
Infrared Technology
基金
南京理工大学自主科研专项计划资助项目
编号:2010ZDJH12
