MSIM: A Multiscale Iteration Method for Aerial Image and Satellite Image Registration
Year: 2025
Type: article
Abstract: The registration of aerial images and satellite images is a key step in leveraging complementary information from heterogeneous remote sensing images. Due to the significant intrinsic differences, such as scale, radiometric, and temporal differences, between the two types of images, existing multimodal registration methods tend to be either inaccurate or unstable when applied. This paper proposes a coarse-to-fine registration method for aerial images and satellite images based on the multiscale iteration method (MSIM). Firstly, an image pyramid is established, and feature points are extracted based on phase congruency. Secondly, the expression form of image descriptors is improved to more accurately describe image feature points, thereby increasing the matching success rate and achieving coarse registration between images. Finally, multiscale iterations are performed to find accurate matching points from top to bottom to achieve fine registration between images. In order to verify the effectiveness and accuracy of the algorithm, this paper also establishes a set of registration datasets of aerial and satellite captured images. Experimental results show that the proposed algorithm has high accuracy and good robustness, and effectively solves the problem of registration failure in existing algorithms when dealing with heterogeneous remote sensing images that have large scale differences.
Source: Remote Sensing
DOI: 10.3390/rs17081423
Authors: Xiaojia Liu, Yalin Ding, Chongyang Liu
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W4409502532