Detecting streaks in smart telescopes images with Deep Learning

Fuente: arXiv
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Main Authors: Parisot, Olivier, Jaziri, Mahmoud
Format: Preprint
Published: 2025
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author Parisot, Olivier
Jaziri, Mahmoud
author_facet Parisot, Olivier
Jaziri, Mahmoud
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2510_17540
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Detecting streaks in smart telescopes images with Deep Learning
Parisot, Olivier
Jaziri, Mahmoud
Instrumentation and Methods for Astrophysics
Computer Vision and Pattern Recognition
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.
title Detecting streaks in smart telescopes images with Deep Learning
topic Instrumentation and Methods for Astrophysics
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2510.17540