A coarse-to-fine image registration method based on visual attention model

Image registration is fundamental and crucial to remote sensing. However getting highly accurate registration performance automatically and fast for large-field images consistently is a challenge. As a work around to this problem, we propose a new image registration concept based on visual attention in this paper. This concept employs the advantages of feature-based or area-based methods to improve the precision and efficiency of image registration. The key concept of proposed integrated scheme is to make optimum use of the highly prominent details in the full scene by means of visual attention computational mechanism. To testify the validation, comparisons with other classical methods are carried out on real-world images. The experimental results show that the proposed method can effectively perform on multi-view/multi-temporal remote sensing images with outstanding precision and time saving performance.