  Recent development of Under-Display Camera (UDC) systems provides a true
bezel-less and notch-free viewing experience on smartphones (and TV, laptops,
tablets), while allowing images to be captured from the selfie camera embedded
underneath. In a typical UDC system, the microstructure of the semi-transparent
organic light-emitting diode (OLED) pixel array attenuates and diffracts the
incident light on the camera, resulting in significant image quality
degradation. Oftentimes, noise, flare, haze, and blur can be observed in UDC
images. In this work, we aim to analyze and tackle the aforementioned
degradation problems. We define a physics-based image formation model to better
understand the degradation. In addition, we utilize one of the world's first
commodity UDC smartphone prototypes to measure the real-world Point Spread
Function (PSF) of the UDC system, and provide a model-based data synthesis
pipeline to generate realistically degraded images. We specially design a new
domain knowledge-enabled Dynamic Skip Connection Network (DISCNet) to restore
the UDC images. We demonstrate the effectiveness of our method through
extensive experiments on both synthetic and real UDC data. Our physics-based
image formation model and proposed DISCNet can provide foundations for further
exploration in UDC image restoration, and even for general diffraction artifact
removal in a broader sense.
