云杂波背景弱小目标自适应时-空域滤波检测研究  

Adaptive Spatial-temporal Filters for Dim Small Targets Detection in Evolving Cloud Clutter

作　　者：陈尚锋[1] 卢焕章[1] 

机构地区：[1]国防科学技术大学ATR国防重点实验室,湖南长沙410073

出　　处：《激光与红外》2008年第7期723-726,共4页Laser & Infrared

摘　　要：针对复杂云背景成像弱小目标实时检测的需要,提出一种检测能力强、易实现的自适应时-空级联滤波目标检测算法,其中时域滤波采用改进的可递归实现的方差滤波器预检测出包含目标和少量杂波点在内的可疑目标点集,而后通过一种自适应像素空域边缘强度滤波器剔除剩余杂波点。算法两级滤波器的参数均实时更新,因此算法对场景变化适应能力强。对五组实际红外图像序列目标检测的实验结果表明,算法能稳定检测出多类天空背景中的目标。Real-time dim small targets detection in heavy cloud clutter is one of the key techniques of infrared search and track （IRST） system. An efficient and practical adaptive spatial-temporal filtering targets detection algorithm is proposed. At first a modified recursive adaptive temporal variance filter is employed to reject most background pixels and detect candidate targets which include few cloud edge pixels. After preprocessing an adaptive spatial filter proceeds to eliminate the residual clutter pixels according to their larger pixel-edgy intensity versus targets. This detection algorithm updates parameters as new frame arrived, thus is robust to scene variation. The usefulness of the algorithm is tested using five kinds of real-world IR image sequence with different background characteristics and proved to be effective and robust.

关 键 词：弱小目标检测 红外图像序列 云杂波 自适应滤波 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]