摘要
提出一种融合多元模糊空间关系信息的支撑树搜索算法,即S Prim(spatialPrim)算法,用以识别低分辨率环境下(红外、多光谱遥感、SAR、恒星导航等图像中)具有规则空间分布关系的目标斑点集合。S Prim算法将子目标相互之间的空间分布关系、距离关系,以及目标自身属性关系进行模糊信息融合,借助Prim算法生成最小支撑树的机制,评估邻近节点之间可能具备的某些有规则的空间分布关系,主动探测子目标之间可能存在的空间分布规律,从而识别目标群。实验证明,该算法稳定有效。
To recognize the arrays, a novel spatial relationship detection algorithm of blob targets' array at a low resolution context (infrared, remote-sensing multi-spectrum, SAR and star navigation. images) is presented. i.e., the S-Prim (spatial Prim) algorithm which is a kind of Prim MST algorithm that integrates spatial relationship information. The algorithm integrates spatial information by estimating the regular spatial relationship among neighboring nodes by back-searching the path in the found tree and forward-detecting the nearest nodes. The detected tree can be considered as the evaluation of reqular spatial relationship, and some of its features can be used to detect the arrays. The experiments show that the algorithm is effective and stable.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2005年第3期550-554,共5页
Systems Engineering and Electronics
基金
"十五"国防预研基金资助课题(41303040204)
