Eliminating artefacts in Polarimetric Images using Deep Learning

Understand

Polarization measurements done using Imaging Polarimeters such as the Robotic Polarimeter are very sensitive to the presence of artefacts in images.

• Artefacts can range from internal reflections in a telescope to satellite trails that could contaminate an area of interest in the image.
• With the advent of wide-field polarimetry surveys, it is imperative to develop methods that automatically flag artefacts in images.
• In this paper, we implement a Convolutional Neural Network to identify the most dominant artefacts in the images.