关键词: 图像配准, 归一化互信息, 非均匀随机抽样原则

Abstract: When images are aligned by non-uniform subsampling methods based on intensity probability distribution and gradient information of floating image, the subsampling strategies on pixels with the same intensity and gradient will change the subsampling results and then change registration process. The registration measure’s curved surfaces and convergence are compared by applying six subsampling strategies to rigid image registration under several subsampling rates. The results of tests show that the non-uniform stochastic subsampling strategy outperforms other subsampling strategies in convergence and anti-noise performance of the normalized mutual information.

Key words: image registration, normalized mutual information, non-uniform stochastic subsampling strategy