Automatic image registration by extraction of interested sub-region

摘要

With the recent increase in the amount of remote sensing images and the corresponding interest in temporal change detection, image registration has become increasingly important as a necessary first step in the integration of multi-temporal or multi-source data, for applications such as the analysis of seasonal and annual global climate changes, as well as land cover changes. Ground Control Point method can be subjective and extremely time-consuming as a result of manual selection of the control point pairs. The intensity-based registration is a solution to this problem. To the larger size images, however, the computational load can be high. In this paper, we develop a new automated registration approach to combine the advantage of two methods. First, a mathematical morphology-based method is used to extract interested sub-region pairs from the reference and floating image. Next, the registration of sub-region pairs is implemented by mutual information. At last the global transformation result will originate from the registration results of these sub-region pairs. By experiment on the larger size remote sensing images, less registration time and subpixel accuracy of registration results can be obtained, which reveal that the proposed registration algorithm is a robust solution.