Image registration based on criteria of feature point pair mutual information

Similarity measurement based on mutual information maximisation has been successful applied in image registration. However, it costs a lot of computation time and the interference of local maxima in the search process always makes the registration search into local maxima that may cause misregistration. In order to eliminate these shortcomings, a novel image registration method is presented in this study. In the method wavelet multi-scale product is calculated to extract the feature points and angle information of the two input images, then a new criterion of registration criterion of feature point pair mutual information is defined to acquire corresponding matching points. In the experiments, our method and image registration methods based on correlation criteria and alignment metric criteria are tested for comparison. Experimental results show that the registration of our method outperforms that of the other two methods and the registration errors are obviously reduced. The errors of coordinates are lower compared to the errors of 78% of the other two methods and the errors of rotation angle are lower compared to the errors of 6% of the other two methods. The seams of the registration image results are very smooth and the transition zones are very uniform.