期刊文献+

图像配准中图像互信息的快速估计算法

Fast estimation algorithm of image mutual information for image registration
下载PDF
导出
摘要 快速、精确地估计图像互信息是图像配准中一个非常重要的课题,它涉及到两幅图像的联合概率密度和边缘概率密度的估计。针对核密度估计法运算量大而导致互信息估计速度慢的问题,提出了一种快速核密度估计法,并用它估计图像互信息。快速算法利用了单位冲激函数性质和基于快速傅立叶变换的快速卷积算法,能在线性时间复杂度内估计互信息。采用临床MRI图像的实验证实了快速算法的性能。 To estimate mutual information of images rapidly and accurately is one of very important problem in image registration,which involves estimating joint probability density and marginal probability density of two images.Kernel Density Estimator (KDE),however,is computational expensive.This makes it very slow to compute mutual information.In this paper,a fast estimation algorithm is presented which takes advantage of the property of delta function and fast convolution based on fast Fourier transform.The proposed algorithm can estimate mutual information of images with linear time complexity.Experiments show the fast algorithm is very efficient.
出处 《计算机工程与应用》 CSCD 北大核心 2008年第13期164-167,共4页 Computer Engineering and Applications
关键词 互信息 核密度估计 图像配准 快速卷积 mutual information kernel density estimator image registration fast convolution
  • 相关文献

参考文献11

  • 1Viola P,Wells W.Alignment by maximization of mutual information[C]//Proceedings of the 5th International Conference on Computer Vision.Boston,MA, USA:IEEE, 1995 : 16-23.
  • 2Collignon A,Maes F,Vandemaeulen D,et al.Automated multimodality image registration using information theory[C]//Proceedings of the Information Processing in Medical hnaglng Conference.Brest, France : Kluwer Academic Publishers, 1995 : 263-274.
  • 3Pluim J P W,Maintz J B A,Viergever M A.hnage registration by maximization of combined mutual information and gradient information[J].IEEE Trans Med, hnaging, 2000, 19( 8 ) : 809-814.
  • 4Russakoff D B,Tomasi C,Maurer J,et al.hnage similarity using mutual information of regions[C]//Proceedings of the 8th European Conference on Computer Vision ( EC CV ).Prague : Springer, 2004:596- 607.
  • 5Studhohne C,Hill D L G,Hawkes D J.An overlap invariant entropy measures of 3D medical image alignment[J].Pattern Recognition, 1999,32( 1 ):71-86.
  • 6Rueekert D,Clarkson M J,Hill D L G.Non-rigid registration using higher-order mutual information[C]//Proceedings of SPIE Medical hnaging 2000, Bellingham, WA, 2000,3979 : 438-447.
  • 7COVER TM,THOMAS JA.信息论基础[M].阮吉寿,张华,译.北京:机械工业出版社,2005:40-41.
  • 8de la Rosa J I,Fleury G.On the kernel selection for minimum-entropy estimation[C]//Proceedings of the IEEE Instrumentation and Measurement Technology, 2002 ( 2 ) : 1205-1210.
  • 9Rosenblatt M.Remarks on some nonparametric estimates of a density function[J].Annals of Mathematical Statistics, 1956,27(6) : 832- 837.
  • 10Parzen E.On estimation of a probability density function and model[J].Annals of Mathematical Statistics, 1962,33(8): 1065-1076.

共引文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部