  Under-display camera (UDC) is a novel technology that can make digital
imaging experience in handheld devices seamless by providing large
screen-to-body ratio. UDC images are severely degraded owing to their
positioning under a display screen. This work addresses the restoration of
images degraded as a result of UDC imaging. Two different networks are proposed
for the restoration of images taken with two types of UDC technologies. The
first method uses a pyramidal dilated convolution within a wavelet decomposed
convolutional neural network for pentile-organic LED (P-OLED) based display
system. The second method employs pyramidal dilated convolution within a
discrete cosine transform based dual domain network to restore images taken
using a transparent-organic LED (T-OLED) based UDC system. The first method
produced very good quality restored images and was the winning entry in
European Conference on Computer Vision (ECCV) 2020 challenge on image
restoration for Under-display Camera - Track 2 - P-OLED evaluated based on PSNR
and SSIM. The second method scored fourth position in Track-1 (T-OLED) of the
challenge evaluated based on the same metrics.
