基于分形和粗集理论的云杂波背景下序列图像弱目标检测  

Weak Targets Detection in Cloud Clutter Image Sequences Based-on Fractal and Rough Set Theory

作　　者：闫晓珂[1] 史彩成[1] 赵保军[1] 何佩琨[1] 

机构地区：[1]北京理工大学信息科学技术学院电子工程系

出　　处：《北京理工大学学报》2006年第9期824-827,共4页Transactions of Beijing Institute of Technology

基　　金：国家部委预研项目(2002AA803032)

摘　　要：提出了云杂波背景下序列图像中弱目标检测新方法.基于粗糙集理论建立了云杂波背景下弱目标检测模型,使之符合两种不同图像边缘的局部分形维的奇异值改变,根据目标和背景的时域特征完成目标检测.实验及仿真结果表明,该算法能够抑制空间和时间相关性强的云杂波背景,且算法简单.A new method for the detection of moving dim targets in cloud clutter image sequences is proposed. A detection model of weak targets in cloud clutter background is established based on indiscernibility relation of rough sets （RS） theory, according to the concept that singular local fractal dimension （LFD） will be determined at edges even if the two segments incident to the edge have the same LFD, and the target is detected according to the difference in the temporal of cloud clutter and weak target. Simulation and the experimental results showed that the algorithms are effective in suppressing cloud clutters strongly spatial and temporal related, and they are easy to be implemented.

关 键 词：分形 粗集理论 云杂波图像 弱目标检测 

分 类 号：TN911.73[电子电信—通信与信息系统]