Image Registration Based on Improved Mutual Information with Hybrid Optimizer
TANG Min
摘要：An improved image registration method is proposed based on mutual information with hybrid optimizer. Firstly, mutual information measure is combined with morphological gradient information. The essence of the gradient information is that locations with a large gradient magnitude should be aligned, but also the orientation of the gradients at those locations should be similar. Secondly, a hybrid optimizer combined PSO with Powell algorithm is proposed to restrain local maxima of mutual information function and improve the registration accuracy to sub-pixel level. Lastly, multiresolution data structure based on Mallat decomposition can not only improve the behavior of registration function, but also improve the speed of the algorithm. Experimental results demonstrate that the new method can yield good registration result, superior to traditional optimizer with respect to smoothness and attraction basin as well as convergence speed.
机标关键词：mutual informationgradient informationimage registrationPowell algorithmattraction basindata structurenew method
分类号：TP391(计算技术、计算机技术)R445(诊断学)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：8( 18-25 )
英文信息