摘要
提出一种基于最小概率距离和改进部分体积(PV)插值的图像配准方法。采用Powell优化算法迭代搜索对称KL距离的最小值,获取最小概率距离,将其作为配准测度,并利用改进的PV插值算法提高图像配准的鲁棒性。实验结果表明,与基于互信息的图像配准方法相比,该方法能有效地减少耗费时间,提高配准精度。
This paper presents a new image registration method based on minimal probability distance and improved Partial Volume（PV） interpolation.Powell optimization algorithm is used to search the symmetric Kullback Leibler（KL） distance to get the minimal probability distance,which is used to be the criteria of registration.An adaptive PV interpolation method is given to improve the robustness of registration.Experimental result shows that this method can effectively reduce the time cost and improve the correctness of registration compared to the method based on mutual information.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第21期188-190,共3页
Computer Engineering
基金
国家自然科学基金资助项目(61070118)
关键词
互信息
图像配准
最小概率距离
部分体积插值
Powell优化
Mutual Information（MI）
image registration
minimal probability distance
Partial Volume（PV） interpolation
Powell optimization
