fiDrizzle-MU: A Fast Iterative Drizzle with Multiplicative Updates

Abstract

We propose fiDrizzleMU, an algorithm for co-adding exposures via iterative multiplicative updates, replacing the additive correction framework. This method achieves superior anti-aliasing and noise reduction in stacked images. When applied to James Webb Space Telescope data, the fiDrizzleMU algorithm reconstructs a gravitational lensing candidate that was significantly blurred by the pipeline's resampling process. This enables the accurate recovery of faint and extended structures in high-resolution astronomical imaging.

12 pages, 5 figures, published in RAA