摘要
针对复杂背景下红外运动小目标的检测和跟踪存在的难点,提出了基于SUSAN检测思想的滤波方法。该方法是通过构建局部区域的奇异性函数来计算奇异度的,并借鉴Wiener滤波的思想,由最小绝对差确定出灰度差阈值。该滤波方法达到了抑制背景、提高信噪比的目的。
For solving the problem of detection and track of infrared small dim target under complicated cloudy background, a new filter algorithm based on improved SUSAN principle is prop（wed. This algorithm is used to calculate the singularity degree by constructing singularity function of local region and for reference Wiener filter to calculate gray difference threshold by the minimum of absolute dispersion. This filter algorithm achieves the goal of restraining the background and raising SNR.
出处
《光学技术》
EI
CAS
CSCD
北大核心
2007年第2期163-165,169,共4页
Optical Technique
关键词
图像处理
小目标检测
奇异度
复杂背景
image processing
small target detection
singularity degree
complicated background
