SOURCE-LINKED INTELLIGENCE

Benchmarking RAW and RGB Restoration in Image Signal Processors

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Modern cameras transform RAW sensor measurements into sRGB images through an image signal processor (ISP). We benchmark two placements for blind restoration around a fixed ISP: (A) pre-ISP restoration in the RAW domain and (B) post-ISP restoration in the sRGB domain. The benchmark covers four smartphone device groups, two learned ISPs, three degradation regimes--noise, blur, and joint noise and blur--, and several representative RAW and RGB restoration models. Our results show that placement alone does not determine performance. The RAW restoration strategy outperforms the best generic RGB res

Read original source ↗ Open in workspace

recordType

paper

region

Global