摘要
红外探测器受到各种外因、内因的干扰,导致成像模糊,噪声干扰大,使红外运动小目标检测技术成为一直难以实现突破的尖端技术难题,本文提出综合运用基于小波变换的高频信息提取算法、基于灰度形态学梯度的边缘检测算法和以圆形性特征量作为判决准则的边界提取算法的红外运动小目标检测算法。
Infrared detectors are interfered by varying external and internal factors, which leads to obscure imaging and huge noise jamming. Infrared moving small-target detection techniques have become difficult sophisticated technique problems to make a breakthrough in. An algorithm was tested, which synthesizes the algorithm of high frequency information extraction by small wavelet transform, the algorithm of edge detection on gray mathematical morphology, and the algorithm of boundary extraction with the rule of rotundity-like character measure.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2006年第z2期747-749,共3页
Journal of System Simulation
基金
国防预研项目资助(103020305)
关键词
红外探测器
红外运动小目标检测技术
小波变换
灰度形态学
圆形性特征量
infrared detector
infrared moving small-target detection techniques
small wavelet transform
gray mathematical morphology
rotundity-like character measure
作者简介
曹素平(1979-),女,安徽东至人,硕士,助教,研究方向为数字图像处理与模式识别; 李俊山(1956-),男,陕西白水人,博士,教授,研究方向为数字图像处理与模式识别、网络信息技术与信息安全等.
