摘要
针对基于局部结构特征的图像配准算法对特征描述不够精确、外点剔除过程运算复杂度高的问题,提出了一种利用空间序列描述子的快速准确的图像配准算法。算法定义了一种基于空间序列的特征点描述子,通过定义特征点间的连接权值和排列顺序构成点的特征来描述,融合了图像局部结构和全局信息;通过对随机采样一致性检验的改进,采用投票策略和随机采样一致性检测的方法,解决外点剔除问题;利用空间序列描述子进行图像配准,通过配准和外点剔除交替迭代进一步提高配准精度。定量分析与实验结果表明:与传统的特征点匹配算法相比,该算法具有结构简单、易于实现的特点,具有配准精度高和计算时间少的优点,具有较高的复现率和准确率。
A fast and accurate image registration algorithm using the spatial order descriptor is proposed to improve existing image registration algorithms based on local structures that have the shortcomings of low registration accuracy on feature description and expensive computation on outlier removing.A simple shape descriptor for feature points is defined,and the definition is based on the space geometrical properties,uses the connective weights among the points and their rank order,and integrates the local structure and global information of the image.An efficient method to remove outlier is given to improve the registration accuracy,and the method is based on an improved random sample consistency test strategy.The registration accuracy is further improved by iteratively performing outlier removing and image registration.Experimental results show that the proposed algorithm has high registration accuracy and low computational cost.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2014年第6期19-24,共6页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(61271293/F010305)
关键词
图像配准
图像特征点
空间序列描述子
随机采样一致性
image registration
image feature point
spatial order descriptor
random sample consensus