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Advancing Earth observation: a survey on AI-powered image processing in satellites

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Publicado en:European Journal of Remote Sensing vol. 58, no. 1 (Dec 1, 2025)
Autor principal: Duggan, Aidan
Otros Autores: Andrade, Bruno, Afli, Haithem
Publicado:
Taylor & Francis Ltd.
Materias:
Artificial intelligence
Satellites
Satellite observation
Earth
Constraints
Image processing
Satellite imagery
Deep learning
Computer science
Data processing
Landsat satellites
Artificial satellites
Machine learning
Communication channels
Remote sensing
Edge computing
Sensors
Cost control
Ground stations
Environmental
Acceso en línea:Citation/Abstract
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Resumen:ABSTRACT 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.
ISSN:2279-7254
1129-8596
2039-7879
DOI:10.1080/22797254.2025.2567921
Fuente:Research Library