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典型相关分析在图像匹配技术中的应用研究
引用本文:方建斌,管琼,王雨春.典型相关分析在图像匹配技术中的应用研究[J].江汉大学学报(自然科学版),2010,38(4):66-69.
作者姓名:方建斌  管琼  王雨春
作者单位:[1]江汉大学数学与计算机科学学院,湖北武汉430056 [2]武汉理工大学理学院,湖南岳阳414006 [3]湖南理工学院信息与通信工程学院,湖北武汉430070
摘    要:典型相关分析是多元统计分析的一个重要研究课题,它借助主成分的思想,用少数几对综合变量来反映两组变量间的线性相关性质.文章采用典型相关分析方法,对相邻图像进行匹配拼接,确定出合适的拼接点,并选用不同场景的图像进行试验,取得了较好的结果.

关 键 词:典型相关分析  核理论  图像匹配

Application of Canonical Correlation Analysis on Image Matching
FANG Jian-bin,GUAN Qiong,WANG Yu-chun.Application of Canonical Correlation Analysis on Image Matching[J].Journal of Jianghan University:Natural Sciences,2010,38(4):66-69.
Authors:FANG Jian-bin  GUAN Qiong  WANG Yu-chun
Institution:1.School of Mathematics and Computer Science,Jianghan University,Wuhan 430056,Hubei,China;2.School of Information and Communication Engineering,Hunan Institute of Science and Technology,Yueyang 414006,Hunan,China;3.School of Science,Wuhan University of Technology,Wuhan 430070,Hubei,China)
Abstract:Canonical Correlation Analysis(CCA) is an important subject of multivariate stat-istical analysis.Based on the idea of principal component analysis,the linear correlation between two sets of variables is reflected with a few basis vectors.By means of CCA,the appropriate con-nection points are determined to match adjacent images,different scenes are selected to modify the image,and good result is obtained.
Keywords:Canonical Correlation Analysis(CCA  ) kernel method belief value  image matching
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