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Research PaperResearchia:202603.20030[Biomedical Engineering > Engineering]

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 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

Submission:3/20/2026
Comments:0 comments
Subjects:Engineering; Biomedical Engineering
Original Source:
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arXiv: This paper is hosted on arXiv, an open-access repository
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GenMFSR: Generative Multi-Frame Image Restoration and Super-Resolution | Researchia