事件相机让卫星感知更高效,低功耗高动态捕捉变化
Event-Based Vision in Space: Applications, Trends, and Future Directions

- 用异步事件捕捉光照变化,省电且无运动模糊
- 微秒级响应,支持高速和复杂环境下的观测
- 适合对功耗敏感的航天任务与实时处理场景
地球观测正因新型传感技术部署而深刻变革。传统帧式光学传感器在轨道环境中常面临运动模糊、高功耗和极端数据冗余问题。相比之下,事件相机(又称类脑摄像头)采用生物启发的异步机制,仅记录局部亮度变化,实现微秒级时间分辨率、极高的动态范围和出色的能效。尽管这类传感器正从地面系统快速扩展至轨道平台,其空间应用的文献仍高度分散。本文综述了事件视觉在太空领域的研究现状,基于现有文献提出四维分类体系:1)大气与高速观测;2)环境监测与变化检测;3)运行支持与星上处理;4)地理空间建模与预测分析。研究表明,类脑工程不仅是补充成像手段,更是一种范式革新,可直接应对现代遥感与可持续太空探索中的关键瓶颈。
原文摘要 · Abstract (English)
Earth Observation (EO) is undergoing a significant transformation driven by the deployment of novel sensing technologies. Traditional frame-based optical sensors often struggle with motion blur, high power consumption, and extreme data redundancy in challenging orbital environments. In contrast, event-based sensors, also known as neuromorphic cameras, offer a bio-inspired asynchronous approach. By capturing only local illumination changes, they provide microsecond temporal resolution, an extremely high dynamic range, and exceptional energy efficiency. Although the use of these sensors is rapidly expanding from terrestrial systems to orbital platforms, the scientific literature surrounding their space-based applications remains heavily fragmented. To bridge this gap, this article presents a comprehensive review of the state-of-the-art in event-based vision in the space domain. Based on the retrieved literature, we introduce a taxonomy structured around four primary domains: 1) atmospheric and high-speed observation; 2) environmental monitoring and change detection; 3) operational support and onboard processing; and 4) geospatial modeling and predictive analysis. As a result, this survey highlights that neuromorphic engineering is far more than a supplementary imaging technique; it is a paradigm shift that can be used to directly address critical bottlenecks in modern remote sensing and sustainable space exploration.
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