综述星载AI图像处理技术，解决卫星数据传输瓶颈
Advancing Earth Observation: A Survey on AI-Powered Image Processing in Satellites
- 系统梳理星载AI图像处理的挑战与应对策略
- 总结当前在轨处理的典型方法与性能表现
- 适合遥感、AI硬件与航天工程方向研究者参考
技术进步与成本降低推动地球观测（EO）卫星影像质量和数量的显著提升。这给传统将影像传回地面再处理的工作流程带来了效率挑战。一种解决方案是利用预训练的人工智能模型在卫星上进行图像处理，但受限于卫星环境中的资源约束，实施难度大。本文全面回顾了近年来关于地球观测卫星上图像处理的研究进展，详细分析了主要限制因素，并总结了最新的缓解策略。
原文摘要 · Abstract (English)
Advancements in technology and reduction in it's cost have led to a substantial growth in the quality & quantity of imagery captured by Earth Observation (EO) satellites. This has presented a challenge to the efficacy of the traditional workflow of transmitting this imagery to Earth for processing. An approach to addressing this issue is to use pre-trained artificial intelligence models to process images on-board the satellite, but this is difficult given the constraints within a satellite's environment. This paper provides an up-to-date and thorough review of research related to image processing on-board Earth observation satellites. The significant constraints are detailed along with the latest strategies to mitigate them.
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