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Advancements in technology and a reduction in its cost have led to substantial growth in the quality and 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 address this issue is to use pre-trained artificial intelligence models to process images onboard 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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Duggan et al. (2025) studied this question.
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