出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Digital images often contain “noise” which takes away their clarity and sharpness. Most of the
existing denoising algorithms do not offer the best solution because there are difficulties such as
removing strong noise while leaving the features and other details of the image intact. Faced
with the problem of denoising, we tried solving it with a Convolutional Neural Network
architecture called the “U-Net”. This paper deals with the training of a U-Net to remove 3
different kinds of noise: Gaussian, Blockiness, and Camera shake. Our results indicate the
effectiveness of U-Net in denoising images while leaving their features and other details intact.
