CVIVApr 24, 2024

Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey

arXiv:2404.16223v119 citationsh-index: 982024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Originality Synthesis-oriented
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It addresses the under-explored problem of RAW image super-resolution for modern Image Signal Processing pipelines, but is incremental as it surveys existing methods from a challenge.

This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, which tackled the problem of upscaling RAW Bayer images by 2x with unknown degradations like noise and blur, and reports the results of the top-5 submissions as a benchmark for current state-of-the-art.

This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is to upscale RAW Bayer images by 2x, considering unknown degradations such as noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. The performance of the top-5 submissions is reviewed and provided here as a gauge for the current state-of-the-art in RAW Image Super-Resolution.

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