Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution

Understand

Real-world image super-resolution (Real SR) aims to generate high-fidelity, detail-rich high-resolution (HR) images from low-resolution (LR) counterparts.

• Existing Real SR methods primarily focus on generating details from the LR RGB domain, often leading to a lack of richness or fidelity in fine details.
• In this paper, we pioneer the use of details hidden in RAW data to complement existing RGB-only methods, yielding superior outputs.
• We argue that key image processing steps in Image Signal Processing, such as denoising and demosaicing, inherently result in the loss of fine details in LR images, making LR RAW a valuable information source.