摘要
针对红外弱小多目标图像背景杂波干扰严重、弱小目标检测率低和目标跟踪困难的问题,提出一种基于噪声方差估计的红外弱小目标快速检测与目标跟踪算法。首先采用改进的形态学滤波抑制背景噪声,对处理后的多帧图像进行方差估计初步突出目标像素;然后对其进行信噪比(SNR)估计得到整个图像序列像素得分,图像中像素SNR高的被标记为目标像素;再对标记过的图像进行分块分析,准确提取出连续图像序列中的目标像素;将检测出的目标像素作为Hough变换的目标跟踪算法的输入,设置双阈值实现目标的有效跟踪。实验结果表明,在复杂背景下的红外弱小目标提取中,基于噪声方差估计的目标检测拥有较高的检测概率和较低的虚警概率,将其获得的目标像素作为Hough变换的输入,不仅可以有效跟踪目标,而且简化了算法的复杂度,实现目标的快速提取和跟踪,具有很高的应用价值。
An algorithm on fast detection and tracking of weak infrared targets from comple x background is proposed based on noise variance estimation.Firstly,the backgro und noise is suppressed by the improved morphological filtering,and the target pixel is hig hlighted preliminarily by the variance estimation of the processed multi-frame image,th en the signal-to-noise natio （SNR） is estimated to get the whole image sequence pixel score.The pixels with high scor es are marked as the target pixels,and the marked image is divided and analyzed.Finally,th e target pixels in the continuous image sequence are extracted accurately.The target pixels are de tected as the input of the target tracking algorithm of the Hough transform,and the double-th reshold is set to achieve the effective tracking of the target.The experimental results show t hat the target detection based on the noise variance estimation has a high detection probabilit y and a low false alarm probability in the infrared small target extraction under complex backgrou nd,and the target pixels obtained as the input of the Hough transform can not only effectiv ely track the target,but also simplify the complexity of the algorithm to achieve rapid extra ction and tracking of targets.
作者
王军
姜志
孙慧婷
张新
何昕
WANG Jun1,3 , JIANG Zhi2 , SUN Hui-ting1 , ZHANG Xin3 , HE Xin3(1. School of Electronic ＆ Information Engineering,Suzhou University of Science and Technology ,Suzhou 215009, China ; 2. Center of Arms Experiment of Baicheng, Baicheng 137000,China; 3. Changchun Institute of Optics, Fine Mechanics and Physics,Chinese Academy of Science,Changchun 130033, Chin)
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2018年第3期305-313,共9页
Journal of Optoelectronics·Laser
基金
江苏省建设系统科技项目(2017ZD84)、苏州市科技发展计划(重点实验室)(SZS201609)和江苏省企业研究生工作站资助项目
关键词
方差估计
形态学滤波
阈值
目标检测
variance estimation
morphological filtering
threshold
target detection
