Image alignment plays a crucial role in solar physics research, primarily involving translation, rotation, and scaling. \G{ 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. \G{ 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 { \AA} of the Atmospheric Imaging Assembly (AIA), the 1216 { \AA} of the Solar Disk Imager (SDI), and the 465 { \AA} 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 (UABJM). \G{ The evaluation results indicate that this approach achieves sub-pixel accuracy in the alignment of AIA 304 { \AA} and SDI 1216 { \AA}, while demonstrating higher accuracy in the alignment of AIA 304 { \AA} and SUTRI 465 { \AA}, which have greater similarity.
Categories: astro-ph.IM astro-ph.SR