Comparison of Correlation-Based Techniques for Correcting and Stacking Solar Magnetic-Field Images

In observing solar magnetic field, which can be as weak as a few Gausses, multiple short-exposure images usually need to be stacked for obtaining images of high signal-to-noise ratios(SNR). In short-exposure images there are linear-coordinate displacements due to influence of atmospheric turbulences and wind. Direct stacking of these can smooth away features of a few Gausses. Image correction and stacking techniques thus need to applied. We compare and analyze two algorithms for the purpose, the phase correlation method and phase cross-correlation method. We use the methods to process simulated data and eight sets of actual images of solar magnetic fields. The processing results are evaluated through certain parameters, including the average and standard deviation of error images, the correlation value between reference and shifted images, the entropies of stacked images, and the image-energy values of the magnetic-field images. The results show that the cross-correlation method is less sensitive to noise and faster. It implies that the cross-correlation method is more suitable for correcting and stacking real-time solar magnetic-field images.