摘要
提出一种基于核密度估计的时-空域滤波算法,用于红外搜索跟踪系统图像的背景抑制。算法分为空域滤波和时域滤波两部分。在空域滤波中,采用核密度估计算法对背景进行平滑;在时域滤波中,采用核密度估计算法对经过空域滤波后的图像灰度值进行概率计算,判别属于背景残差的灰度值,然后做进一步的滤除。核方法对背景有很好的光滑性且易于计算机实现,实验表明,这种非参方法设计的时-空域滤波算法对背景杂波有非常良好的抑制效果,信噪比也得到明显提高。
A temporal-spatial filtering algorithm based on kernel density estimation structure is presented for infrared image background suppression in infrared search and track system. The algorithm can be divided into spatial filtering and temporal filte- ring. Smoothing process is applied to the background of an infrared image sequence by using the kernel density estimation algo- rithm in spatial filtering. The probability density of the image gray values after spatial filtering is calculated with the kernel densi- ty estimation algorithm in temporal filtering. The background residual and blind pixels are picked out based on their gray values, and are further filtered. The algorithm is validated with a real infrared image sequence. The image sequence is processed by using Fuller kernel filter, Uniform kernel filter and high-pass filter. Quantitatively analysis shows that the temporal-spatial filtering al- gorithm based on the nonparametric method is a satisfactory way to suppress baekground clutter in infrared images. The SNR is significantly improved as well.
出处
《强激光与粒子束》
EI
CAS
CSCD
北大核心
2015年第5期21-26,共6页
High Power Laser and Particle Beams
基金
国家自然科学基金项目(61340018
61271427)
北京市自然科学基金项目(4152045)
关键词
核密度估计
时-空域滤波
红外背景抑制
红外搜索跟踪系统
kernel density estimation
temporal-spatial filtering
infrared background suppression
infrared search and track system
