Detecting streaks in smart telescopes images with Deep Learning

TL;DR

This paper explores the use of deep learning techniques to automatically detect satellite streaks in astronomical images captured by smart telescopes, aiming to improve image quality and data integrity.

Contribution

It introduces adapted deep learning methods specifically designed for streak detection in raw astronomical data from smart telescopes.

Findings

Deep learning models effectively detect satellite streaks in astronomical images.

The approach reduces the need for manual post-processing.

Results demonstrate high accuracy in streak identification.

Abstract

The growing negative impact of the visibility of satellites in the night sky is influencing the practice of astronomy and astrophotograph, both at the amateur and professional levels. The presence of these satellites has the effect of introducing streaks into the images captured during astronomical observation, requiring the application of additional post processing to mitigate the undesirable impact, whether for data loss or cosmetic reasons. In this paper, we show how we test and adapt various Deep Learning approaches to detect streaks in raw astronomical data captured between March 2022 and February 2023 with smart telescopes.