摘要
目前基于区域的图像配准方法不能同时满足宽范围运动参数和高准确度的配准要求。基于图像变换的频域和空间域特性,提出一种运动参数自适应的图像配准方法,设计了旋转参数、平移参数的估计步骤和融合方法。基于仿真实验对参数自适应方法与Vandewalle方法、Keren改进方法的效果进行了比较分析,采用误差的标准差和均方误差两项指标评价配准算法的参数自适应性和配准准确度,参数自适应方法的两项评价指标均低于另两种方法,表明其在宽范围运动参数估计方面有自适应能力和高配准精度。
The performance of some current area-based image registration algorithms declines when image transformation parameters are of both wide range and high precision. Concerning this problem, a parameter-adaptive registration algorithm was proposed based on the natures of image transformation in frequency/space domain, and the estimation steps and fusion method for rotation parameter and shift parameter were designed. A set of simulation experiments were implemented to compare the performance of the proposed algorithm with the Vandewalle＇s and improved Keren＇s. Mean square error and standard deviation of square error were used as evaluation indicators for registration precision and parameters adaptation. The two indicators of the proposed algorithm are lower than those of the other two methods, which means the proposed algorithm has adaptive ability in wide range parameters estimation and high accuracy of registration.
出处
《计算机应用》
CSCD
北大核心
2013年第2期487-490,共4页
journal of Computer Applications
关键词
图像配准
亚像素
运动参数估计
自适应
图像融合
image registration
sub-pixel
motion parameter estimation
adaptive
image fusion
