Retrieval-Augmented Generation-Based Color Restoration for Low-Light Image Enhancement
Recent low-light image enhancement (LLIE) methods have driven brightness and structural fidelity close to that of normally-exposed images, yet their outputs still exhibit systematic color shifts such as greenish skies, yellowish faces, and warm-tinted white objects. We attribute this to end-to-end LLIE training coupling brightness, structure, and color within a single network, leaving the color channels weakly supervised. We recast color restoration as an independent sub-problem and decouple it from brightness enhancement, realizing it as a general-purpose post-processing module built on retrieval-augmented generation (RAG). Rather than relying solely on parametric color priors learned du...
| Authors | Li-Wei Lu, Shaou-Gang Miaou |
|---|---|
| Primary category | eess.IV |
| Published | 8 August 2026 |
| Last updated at source | 8 August 2026 |
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