Contributions of Machine Learning and Image processing to Astronomical data

Abstract

Astronomy is in a data-driven era due to technological advancements in photography and machine learning. This study aims to show the significant contributions of machine learning and computer graphics to the field of astronomy. That is by investigating the process of astronomical data collection by telescopes. It goes in-depth with the steps and different image processing methods in both the spatial and frequency domains. This is while showing some popular machine learning algorithms that are used for studying and analyzing data. The study has shown the significant integration of computer science in astronomy, making it easier to study larger data sets.