MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality
Image quality in modern imaging systems emerges from the coupled effects of the sensor, optics, and computational reconstruction. Ultra-thin metalenses offer a path toward substantial miniaturization of optical modules, but practical designs often exhibit pronounced chromatic and field-dependent aberrations that necessitate computational reconstruction. In current metalens pipelines, reconstruction models are commonly trained and selected using distortion-based fidelity objectives, such as PSNR, yet these proxies can be weakly correlated with human preference and downstream utility, reflecting the well-known perception--distortion trade-off. We introduce MetaRanker, a human-in-the-loop ac...
| Authors | Yujin Park, Haejun Chung, Ikbeom Jang |
|---|---|
| Primary category | cs.CV |
| Published | 28 May 2026 |
| Last updated at source | 29 June 2026 |
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