用深度学习检测智能望远镜图像中的卫星轨迹，提升天文观测数据质量。
Detecting streaks in smart telescopes images with Deep Learning
- 基于2022年3月至2023年2月的原始天文图像，测试多种深度学习方法
- 有效识别图像中由卫星引起的光轨痕迹，减少数据损失与视觉干扰
- 适用于天文爱好者及专业机构的后处理流程，提升图像可用性
卫星在夜空中的可见度日益增加，对天文观测和天文摄影（无论业余或专业）造成负面影响。这些卫星会在观测图像中引入光轨，需额外后期处理以减轻其带来的数据丢失或视觉影响。本文展示了针对2022年3月至2023年2月期间使用智能望远镜采集的原始天文数据，测试并适配多种深度学习方法，用于检测图像中的光轨痕迹。
原文摘要 · Abstract (English)
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.
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