Ai Image Optimization of under Display Meta-Optic-System( I )

Full-screen and all-screen smartphones, with no buttons or borders to interrupt the pure design, have gradually become the mainstream of the cell phone market. For all-screen smartphones, all of the devices should be hidden behind the screen, including front cameras, fingerprint sensors and so on. For example, Apple has received a patent for an under-screen fingerprint sensor based on an acoustic imaging system that would allow users to unlock an iPhone by touching anywhere on the screen. Chinese smartphone makers, Xiaomi and OPPP, also proposed the front-facing camera hidden behind the screen. Although the first range for smartphones with under-screen cameras won’t deliver the best image quality around. It is still a must-do for cell phone industries. This project aims to deliver a total solution for the under-screen camera based on meta-optics technology. The total track of the optical imaging system is limited by the finite thickness of a laptop and a smartphone. Therefore, a flat lens is essential for this application. Here, we will deliver chip-bonding achromatic PB-phase metalens on CMOS sensors for under-screen imaging. The PB-phase metalens, which is a GaN all-dielectric metasurface, is utilized to capture the image of an object with tens centimeters in front of a screen. For improving the image quality of the captured under-screen images suffering from scattering, color rendering, shadow, and so on, a deep 3D Convolutional Neural Network model and training databased will be established as well. According to the above-mentioned purpose, this three-year project is divided into three sub-project: Design of under-screen imaging system: from macro-, micro- to meta-optics; Nanofabrication of low-cost nitride-based metalens on the glass; Al image optimization: database and training model.