摘要
多模态图像配准中常使用互信息作为配准度量,互信息中的联合概率密度函数一般是利用图像灰度对的统计值来代替的,而图像插值可能产生新的灰度对,造成互信息出现局部极值。该文利用一维信号从理论上分析了线性和最近邻两种插值方法对互信息的影响。理论分析表明,线性插值造成互信息局部极值的可能性较小,而最近邻插值会使互信息出现周期性局部极值。试验结果证实了该文的结论。分析结果对基于互信息的多模态图像配准具有理论参考价值。
Mutual information has been used as a similarity metric in medical image registration. The probabilities of mutual information may be estimated by normalization of the joint intensity histogram, which is obtained by binning the intensity pair of the overlapping parts of the reference image and the floating image. However, image interpolation would create new intensity pairs and may cause local maxima of mutual information. In this paper, local maxima of mutual information are analyzed using linear interpolation and near neighborhood interpolation for different resolution images. Analysis results show that mutual information contains less local maxima when linear interpolation is used, and contains local maxima when near neighborhood interpolation is used. Experiments show the validity of the results. All these results are benefit to multimodal medical image registration.
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第10期1782-1785,共4页
Journal of Electronics & Information Technology
基金
广东省自然科学基金(31789)资助课题
关键词
图像配准
互信息
图像插值
Image registration, Mutual information, Image interpolation
