Neural Networks for Advanced Image and Video Super-Resolutions

Abstract

Super-resolution is a technique aimed at improving the resolution of images and videos, providing clearer, sharper, and more detailed visuals. Neural networks, particularly deep learning models, have revolutionized the field of image and video super-resolution, offering state-of-the-art performance in enhancing visual quality. This article explores the application of neural networks in super-resolution, focusing on both image and video enhancement. We discuss the role of convolutional neural networks (CNNs) and generative adversarial networks (GANs) in advancing super-resolution methods, as well as the challenges and future prospects of these technologies