A High-accuracy Alignment Approach for Solar Images of Different Wavelengths

Abstract

Image alignment plays a crucial role in solar physics research, primarily involving translation, rotation, and scaling. The different wavelength images of the chromosphere and transition region have structural complexity and differences in similarity, which poses a challenge to their alignment. Therefore, a novel alignment approach based on dense optical flow (OF) and the RANSAC algorithm is proposed in this paper. It takes the OF vectors of similar regions between images to be used as feature points for matching. Then, it calculates scaling, rotation, and translation. The study selects three wavelengths for two groups of alignment experiments: the 304 Å of the Atmospheric Imaging Assembly (AIA), the 1216 Å of the Solar Disk Imager (SDI), and the 465 Å of the Solar Upper Transition Region Imager (SUTRI). Two methods are used to evaluate alignment accuracy: Monte Carlo simulation and Uncertainty Analysis Based on the Jacobian Matrix. The evaluation results indicate that this approach achieves subpixel accuracy in the alignment of AIA 304 Å and SDI 1216 Å, while demonstrating higher accuracy in the alignment of AIA 304 Å and SUTRI 465 Å, which have greater similarity.