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基于算术-几何均值距离的多模态图像配准
引用本文:时永刚,邹谋炎.基于算术-几何均值距离的多模态图像配准[J].光学技术,2004,30(4):409-412.
作者姓名:时永刚  邹谋炎
作者单位:中国科学院电子学研究所,北京,100080
基金项目:自然科学基金资助项目(60072020),中国科学院科技创新基金资助项目
摘    要:根据图像灰度联合概率分布函数与图像相似程度之间的关系,提出了一种基于算术 几何均值距离的多模态图像配准新测度。与基于信息论的测度不同,新测度不再要求概率分布必须满足连续性的要求。实验结果表明,所提出的新测度比基于信息论的测度具有更强的噪声鲁棒性和计算量更小。

关 键 词:图像配准  多模态图像  配准测度  算术几何均值距离
文章编号:1002-1582(2004)04-0409-04
修稿时间:2003年10月23

Novel similarity measure based on arithmetic-geometric mean distance for multimodal image registration
SHI Yong-gang,ZOU Mou-yan.Novel similarity measure based on arithmetic-geometric mean distance for multimodal image registration[J].Optical Technique,2004,30(4):409-412.
Authors:SHI Yong-gang  ZOU Mou-yan
Abstract:According to the relation between the intensity joint probability distribution function of two images and the similarity between images, a new similarity measure for multimodal image registration is proposed which is based on the distance between the arithmetic mean and the geometric mean of two probability distribution functions. Unlike information theoretic registration measures, the new measure do not require the condition of absolute continuity to be satisfied by the probability distribution involved. The results of experiment show that the new similarity measure is more tolerable to noise and requires less computational cost than the ones based on the information theory.
Keywords:Image registration  multi-modality image  registration measure  distance between arithmetic mean and geometric mean  
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