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低对比度红外图像点目标运动检测方法
引用本文:张永骞,张涛,崔文楠,夏鲁瑞.低对比度红外图像点目标运动检测方法[J].传感器与微系统,2018(1):22-24,28.
作者姓名:张永骞  张涛  崔文楠  夏鲁瑞
作者单位:中国科学院上海技术物理研究所,上海200083;中国科学院大学,北京100049 中国科学院上海技术物理研究所,上海,200083 中国科学院上海技术物理研究所,上海200083;装备学院,北京101416
基金项目:国家"863"计划资助项目
摘    要:对于背景对比度较低的红外图像,若点目标的亮度不明显,加上探测器噪声的影响,很难分辨出红外图像中处于运动状态的点目标.为了解决这一问题,对探测器采集的相邻2幅图像进行基于灰度峰值与傅里叶相位相关算法的图像配准,计算出2幅图像之间的相对平移量;通过对2幅图像的重叠区域进行差分绝对值、高斯低通滤波及二值化运算;分离出运动的点目标.实验结果表明:检测方法可以有效地检测出低对比度红外图像中的运动点目标.

关 键 词:红外图像  图像配准  点目标检测  infrared  image  image  registration  point  target  detection

Method of point target moving detection of low contrast infrared image
ZHANG Yong-qian,ZHANG Tao,CUI Wen-nan,XIA Lu-rui.Method of point target moving detection of low contrast infrared image[J].Transducer and Microsystem Technology,2018(1):22-24,28.
Authors:ZHANG Yong-qian  ZHANG Tao  CUI Wen-nan  XIA Lu-rui
Abstract:For low contrast infrared images,if the brightness of point target is not obvious,and with influence of detector noise,the moving point target is hard to be recognized in infrared image.To solve this problem,image registration based on peak gray and the Fourier phase correlation algorithm is applied to two adjacent images acquired by detector,and this method can work out relative translation between the two images.Moving point object can be separated from the background.By absolute value of difference,the Gaussian low-pass filter algorithm and binarization operation on overlapping areas of the two images.The experimental results show that this method can effectively detect the moving point target in low contrast infrared image.
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