消色差透镜
色差
光学
色阶
光学成像
物理
高光谱成像
光学像差
光谱成像
计算机科学
公制(单位)
伪装
光子学
人工智能
超连续谱
图像处理
医学影像学
成像技术
相位对比成像
自适应光学
杠杆(统计)
球差
失真(音乐)
人工神经网络
计算机视觉
作者
Jinwen Wei,Yunhui Gao,Liangcai Cao
摘要
ABSTRACT Metalenses leverage subwavelength nanostructures to achieve high‐resolution imaging through phase manipulation, offering a flat alternative to traditional refractive and diffractive imaging systems. However, diffraction‐induced chromatic aberration remains a longstanding obstacle to full‐color, large‐scale metalens imaging. In this work, we propose a neural achromatic imaging framework that integrates a meta–achromatic network with a physics‐informed, PSF‐aware mechanism. The meta–achromatic network discovers and exploits cross‐channel image priors through PSF‐aware attention to enable high‐quality achromatic imaging. Experimental results demonstrate a 51% reduction in an introduced image‐based chromatic aberration metric and a 10.19 dB improvement in peak signal‐to‐noise ratio for imaging with a 7‐mm‐aperture metalens. The proposed framework can potentially be extended to other imaging schemes, spectral regimes, and diffractive computational imaging systems, thereby correcting chromatic aberrations and expanding the practical scale of flat optics.
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