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Real-Time Blind Defocus Deblurring for Earth Observation: The IMAGIN-e Mission Approach

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Abstract

This work addresses mechanical defocus in Earth observation images from the IMAGIN-e mission aboard the ISS, proposing a blind deblurring approach adapted to space-based edge computing constraints. Leveraging Sentinel-2 data, our method estimates the defocus kernel and trains a restoration model within a GAN framework, effectively operating without reference images.

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