计算机工程Issue(11)：163-168,6.DOI:10.3969/j.issn.1000-3428.2013.11.037
核空间与二次相关滤波器融合的红外目标检测
Infrared Target Detection of Kernel Space and Quadratic Correlation Filter Fusion
摘要
Abstract
Aiming at the Quadratic Correlation Filter(QCF) associated with kernel space is applied to infrared target detection, this paper proposes KSSQSDF kernel direct mapping algorithm and MPKPCA-SSQSDF kernel feature extraction fusion algorithm. KSSQSDF directly extends QCF from low dimensional space to high dimensional space, thus QCF is transformed to nonlinear correlation filter in kernel space. MPKPCA-SSQSDF first extracts target feature under kernel space, and then the extracted feature vector is used to QCF of low dimensional space for infrared target detection. Through experiment, the difference of detection result and computational complexity are analytically given when KSSQSDF and MPKPCA-SSQSDF are used respectively. The result shows kernel direct mapping algorithm and kernel feature extraction fusion algorithm have the similar detection accuracy, which evidently exceed QCF of low dimensional space. But MPKPCA-SSQSDF kernel feature extraction fusion algorithm does not confine the type of QCF, and has shorter detection time. So it has more extensive application range, and to some extent it can substitute for KSSQSDF kernel direct mapping algorithm.关键词
红外目标检测/核空间/特征提取/二次陒关滤波器/混合概率模型/子空间二次综合判别函数Key words
infrared target detection/kernel space/feature extraction/Quadratic Correlation Filter(QCF)/mixture probabilistic model/Subspace Quadratic Synthetic Discriminant Function(SSQSDF)分类
信息技术与安全科学引用本文复制引用
魏坤,刘密歌..核空间与二次相关滤波器融合的红外目标检测[J].计算机工程,2013,(11):163-168,6.基金项目
西安市科技计划基金资助项目(CXY1134WL39) （CXY1134WL39）
