Advancing Earth Observation: A Survey on AI-Powered Image Processing in Satellites

TL;DR

This paper reviews recent AI-based methods for on-board image processing in Earth Observation satellites, addressing challenges and strategies to improve efficiency given satellite constraints.

Contribution

It provides a comprehensive survey of current research on AI-powered on-board satellite image processing, highlighting recent advancements and mitigation strategies.

Findings

Summarizes key constraints in satellite onboard processing

Details recent AI strategies to overcome these constraints

Highlights future research directions in the field

Abstract

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.