  Image restoration is a technique that reconstructs a feasible estimate of the
original image from the noisy observation. In this paper, we present a U-Net
based deep neural network model to restore the missing pixels on the lunar
surface image in a context-aware fashion, which is often known as image
inpainting problem. We use the grayscale image of the lunar surface captured by
Multiband Imager (MI) onboard Kaguya satellite for our experiments and the
results show that our method can reconstruct the lunar surface image with good
visual quality and improved PSNR values.
