ExplorerBiomedical EngineeringEngineering
Research PaperResearchia:202603.20030

GenMFSR: Generative Multi-Frame Image Restoration and Super-Resolution

Harshana Weligampola

Abstract

Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and enhance resolution. Multi-frame super-resolution is therefore a fundamental problem in camera pipelines. Existing adversarial methods are constrained by the quality of ground truth. We propose GenMFSR, the first Generative Multi-Frame Raw-to-RGB Super Resolution pipeline, that incorporates image priors from foundation mo...

Submitted: March 20, 2026Subjects: Engineering; Biomedical Engineering

Description / Details

Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and enhance resolution. Multi-frame super-resolution is therefore a fundamental problem in camera pipelines. Existing adversarial methods are constrained by the quality of ground truth. We propose GenMFSR, the first Generative Multi-Frame Raw-to-RGB Super Resolution pipeline, that incorporates image priors from foundation models to obtain sub-pixel information for camera ISP applications. GenMFSR can align multiple raw frames, unlike existing single-frame super-resolution methods, and we propose a loss term that restricts generation to high-frequency regions in the raw domain, thus preventing low-frequency artifacts.


Source: arXiv:2603.19187v1 - http://arxiv.org/abs/2603.19187v1 PDF: https://arxiv.org/pdf/2603.19187v1 Original Link: http://arxiv.org/abs/2603.19187v1

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Submission Info
Date:
Mar 20, 2026
Topic:
Biomedical Engineering
Area:
Engineering
Comments:
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