The paper benchmarks two strategies for blind image restoration around a fixed image signal processor (ISP): restoring in the RAW domain before the ISP (pre‑ISP) and restoring in the sRGB domain after the ISP (post‑ISP). Across four smartphone groups, two learned ISPs, and three degradation regimes (noise, blur, and combined noise‑blur), the study finds that RAW restoration generally outperforms generic RGB restoration, but RGB models trained with ISP‑aware supervision achieve the best overall performance. The authors emphasize that restoration performance depends heavily on how well the restoration model aligns with the imaging pipeline, and they recommend reporting restoration placement and ISP‑aware supervision as key experimental factors.
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