Blind technique for point spread function equalization with application to the Multi-Order Solar Extreme Ultraviolet Spectrograph

When combining remote sensing data from multiple instruments or multiple imaging channels, differences in point spread function (PSF) can lead to systematic error. If the PSFs are not well known, then it is difficult to determine which differences in the image data are meaningful for the object being observed and which are artifacts of PSF. Direct PSF measurements can be problematic. For example, in a sounding rocket payload, launch vibrations and acceleration, subsequent operations in micro gravity, and the impact on return to Earth may all affect PSFs. We have developed a blind method to equalize the PSFs of three distinct instrument channels, as found in the Multi-Order Solar Extreme Ultraviolet Spectrograph (MOSES). To validate our technique, we generate three synthetic images with three different PSFs, with some spectrally interesting features. Thence, we demonstrate the successful removal of PSF-induced artifacts is possible, with the genuine spectral features left intact. We also perform blind PSF equalizations on three copies of the same solar image, but with differing PSFs, after applying independent noise to each. The results accurately reproduce corrections performed in the absence of noise, with full knowledge of the PSFs. Finally, we apply PSF equalization to solar images obtained in the 2006 MOSES flight and demonstrate the removal of artifacts.