Multiple Gaussian Mixture Models for Image Registration
Peng Ye, Fang Liu, Zhiyong Zhao · IEICE Transactions on Information and Systems · 2014
Gaussian mixture model (GMM) has recently been applied for image registration given its robustness and efficiency. However, in previous GMM methods, all the feature points are treated identically. By incorporating local class features, this letter proposes a multiple Gaussian mixture models (M-GMM) method for image registration. The proposed method can achieve higher accuracy results with less registration time. Experiments on real image pairs further proved the superiority of the proposed method.