Wei Jinwen, Liu Youhai, Wu Jiachen, Cao Liangcai
Opt Lett. 2024 Sep 1;49(17):4851-4854. doi: 10.1364/OL.531253.
Computational imaging using a Pancake lens can help reduce the size of optical systems by folded optics. However, Pancake cameras frequently exhibit inferior image quality due to stray light, low light transmission, and spatially varying aberrations. In this Letter, we propose a thin and lightweight camera comprising a polarization-based catadioptric Pancake lens and a Fourier Position encoding Network (FPNet). The camera achieves high-quality imaging at an f-number of 0.4 and an expansive 88° field of view. The FPNet encodes the positional order of the point spread functions, mitigating global optical image degradation and improving image quality by 10.13 dB in PSNR. The Pancake camera and FPNet have potential applications in mobile photography and virtual/augmented reality.
使用煎饼透镜的计算成像可以通过折叠光学器件帮助减小光学系统的尺寸。然而，由于杂散光、低光传输和空间变化的像差，煎饼相机的图像质量常常较差。在本信函中，我们提出了一种轻薄型相机，它由基于偏振的折反射煎饼透镜和傅里叶位置编码网络（FPNet）组成。该相机在f数为0.4且视野广阔达88°的情况下实现了高质量成像。FPNet对点扩散函数的位置顺序进行编码，减轻了整体光学图像退化，并使图像质量在峰值信噪比（PSNR）方面提高了10.13 dB。这种煎饼相机和FPNet在移动摄影以及虚拟/增强现实领域具有潜在应用。
