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Recent development of Under-Display Camera (UDC) systems provides a truebezel-less and notch-free viewing experience on smartphones (and TV, laptops,tablets), while allowing images to be captured from the selfie camera embeddedunderneath. In a typical UDC system, the microstructure of the semi-transparentorganic light-emitting diode (OLED) pixel array attenuates and diffracts theincident light on the camera, resulting in significant image qualitydegradation. Oftentimes, noise, flare, haze, and blur can be observed in UDCimages. In this work, we aim to analyze and tackle the aforementioneddegradation problems. We define a physics-based image formation model to betterunderstand the degradation. In addition, we utilize one of the world's firstcommodity UDC smartphone prototypes to measure the real-world Point SpreadFunction (PSF) of the UDC system, and provide a model-based data synthesispipeline to generate realistically degraded images. We specially design a newdomain knowledge-enabled Dynamic Skip Connection Network (DISCNet) to restorethe UDC images. We demonstrate the effectiveness of our method throughextensive experiments on both synthetic and real UDC data. Our physics-basedimage formation model and proposed DISCNet can provide foundations for furtherexploration in UDC image restoration, and even for general diffraction artifactremoval in a broader sense.

Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network