用超薄金属镜头拍出高质量真实场景照片
Enabling High-Quality In-the-Wild Imaging from Severely Aberrated Metalens Bursts
- 用轻量卷积网络+高效融合算法修复金属镜头的模糊和失真
- 在真实手持拍摄中，效果优于现有单图和多图修复方法
- 适合想用超薄镜头实现高画质成像的科研与产品团队
我们解决超薄纳米光子金属镜头相机在真实环境中的成像难题。金属镜头由平面纳米散射阵列构成，相比传统折射光学器件可显著减小尺寸和重量。但严重的色差、强散射、窄谱宽和低光效仍限制其实际应用。本文提出端到端的成像解决方案：将数倍于传统光学器件厚度的金属镜头与专为实用金属镜头相机设计的多图像恢复框架结合。方法核心是一个轻量卷积网络与内存高效的突发融合算法，能自适应校正快速序列中极低质量捕捉下的噪声、过曝截断及镜头畸变。在多种真实手持拍摄数据上的大量实验表明，该方法始终优于现有的突发模式和单图修复技术。结果为金属镜头相机在日常成像应用中的落地提供了可行路径。
原文摘要 · Abstract (English)
We tackle the challenge of robust, in-the-wild imaging using ultra-thin nanophotonic metalens cameras. Meta-lenses, composed of planar arrays of nanoscale scatterers, promise dramatic reductions in size and weight compared to conventional refractive optics. However, severe chromatic aberration, pronounced light scattering, narrow spectral bandwidth, and low light efficiency continue to limit their practical adoption. In this work, we present an end-to-end solution for in-the-wild imaging that pairs a metalens several times thinner than conventional optics with a bespoke multi-image restoration framework optimized for practical metalens cameras. Our method centers on a lightweight convolutional network paired with a memory-efficient burst fusion algorithm that adaptively corrects noise, saturation clipping, and lens-induced distortions across rapid sequences of extremely degraded metalens captures. Extensive experiments on diverse, real-world handheld captures demonstrate that our approach consistently outperforms existing burst-mode and single-image restoration techniques.These results point toward a practical route for deploying metalens-based cameras in everyday imaging applications.
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