Detection and Removal of Artifacts in Astronomical Images

TL;DR

This paper introduces a novel algorithm for detecting and removing transient artifacts in astronomical images, utilizing a deep coadd image and PSF modeling to improve image quality across various seeing conditions.

Contribution

The authors develop a new artifact removal algorithm that effectively cleans single epoch images using a PSF-matched coadd reference, applicable to any survey with multiple observations of the same sky region.

Findings

Effective removal of cosmic rays and satellite trails.

Works well even with images of varying seeing conditions.

Validated on Dark Energy Survey data.

Abstract

Astronomical images from optical photometric surveys are typically contaminated with transient artifacts such as cosmic rays, satellite trails and scattered light. We have developed and tested an algorithm that removes these artifacts using a deep, artifact free, static sky coadd image built up through the median combination of point spread function (PSF) homogenized, overlapping single epoch images. Transient artifacts are detected and masked in each single epoch image through comparison with an artifact free, PSF-matched simulated image that is constructed using the PSF-corrected, model fitting catalog from the artifact free coadd image together with the position variable PSF model of the single epoch image. This approach works well not only for cleaning single epoch images with worse seeing than the PSF homogenized coadd, but also the traditionally much more challenging problem of cleaning single epoch images with better seeing. In addition to masking transient artifacts, we have developed an interpolation approach that uses the local PSF and performs well in removing artifacts whose widths are smaller than the PSF full width at half maximum, including cosmic rays, the peaks of saturated stars and bleed trails. We have tested this algorithm on Dark Energy Survey Science Verification data and present performance metrics. More generally, our algorithm can be applied to any survey which images the same part of the sky multiple times.