Detecting streaks in smart telescopes images with Deep Learning
This addresses the issue for astronomers and astrophotographers, but appears incremental as it applies existing methods to new data.
The paper tackles the problem of satellite streaks contaminating astronomical images by testing and adapting various deep learning approaches to detect these streaks in raw data from smart telescopes.
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.