摘要
根据红外图像中小目标的典型特征提出了一种新的小目标检测算法。利用图像小目标的微分几何特性,计算图像的最小法向曲率,并以此为阈值,获得小目标的候选区对象,以实现目标检测。针对复杂背景下跟踪过程出现背景杂波干扰或目标受到遮挡时,出现目标消失的问题,提出了一种基于概率数据互联滤波器和线性预测技术相结合的实时跟踪算法,以提高目标跟踪的稳定性和精度。最后,利用实际录制的图像序列进行仿真实验,可准确跟踪信噪比不小于2、运动速度为1帧/像素的目标,验证了算法的有效性和实时性。
A new method for small target testing is brought forward aiming at the representative characteristics of small targets in infrared images.In order to realize target detecting,the minimal normal curvature is obtained in use of differential coefficient traits of small targets,and taking this curvature as a threshold,the candidate object of small targets is acquired.Aiming at the target disappears because of background noise or target being sheltered under complex circumstances,the tracking technology for dynamic small targets in serial infrared images is researched,and a real-time tracking algorithm based on probabilistic data association filter （PDAF）and the linear prediction technology is designed so as to improve the stability and precision of target tracking.Finally,the simulation with memorized real time image sequence shows that this algorithm is able to track targets with the signal-to-noise ratio no less than 2 and velocity 1 frame per pixel,which also proves the validity and real-time quality of this algorithm.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2011年第5期978-981,共4页
Systems Engineering and Electronics
基金
国家航空科学基金(20080896009)资助课题
关键词
红外小目标
检测与跟踪
概率数据互联滤波器
线性预测跟踪
法向曲率
infrared small target
detecting and tracking
probabilistic data association filter
linear prediction tracking
normal curvature
