低对比度红外图像点目标运动检测方法

摘要

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.%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.