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

• URL: http://arxiv.org/abs/2505.22128v2
• Date: Wed, 02 Jul 2025 16:31:32 GMT
• Title: Real-Time Blind Defocus Deblurring for Earth Observation: The IMAGIN-e Mission Approach
• Authors: Alejandro D. Mousist,
• Abstract summary: This work addresses mechanical defocus in Earth observation images from the IMAGIN-e mission aboard the ISS.<n>Using Sentinel-2 data, our method estimates the defocus kernel and trains a restoration model within a GAN framework.<n>The approach is currently deployed aboard the IMAGIN-e mission, demonstrating its practical application in an operational space environment.
• Score: 55.2480439325792
• License: http://creativecommons.org/licenses/by/4.0/
• 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. On Sentinel-2 images with synthetic degradation, SSIM improved by 72.47% and PSNR by 25.00%, confirming the model's ability to recover lost details when the original clean image is known. On IMAGIN-e, where no reference images exist, perceptual quality metrics indicate a substantial enhancement, with NIQE improving by 60.66% and BRISQUE by 48.38%, validating real-world onboard restoration. The approach is currently deployed aboard the IMAGIN-e mission, demonstrating its practical application in an operational space environment. By efficiently handling high-resolution images under edge computing constraints, the method enables applications such as water body segmentation and contour detection while maintaining processing viability despite resource limitations.

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