Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …

Image super-resolution (SR) is one of the vital image processing methods that improve the
resolution of an image in the field of computer vision. In the last two decades, significant …

Image Super-Resolution (SR) is an important class of image processing techniqueso
enhance the resolution of images and videos in computer vision. Recent years have …

Video super-resolution (VSR) aims to restore a sequence of high-resolution (HR) frames
from their low-resolution (LR) counterparts. Although some progress has been made, there …

Video super-resolution (VSR) has become even more important recently to provide high
resolution (HR) contents for ultra high definition displays. While many deep learning based …

Recently, several models based on deep neural networks have achieved great success in
terms of both reconstruction accuracy and computational performance for single image …

Convolutional neural networks have made a great breakthrough in recent remote sensing
image super-resolution (SR) tasks. Most of these methods adopt upsampling layers at the …

Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from
the observed LR images. As SR has been developed for more than three decades, both …

Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …

Single image super-resolution (SISR) has played an important role in the field of image
processing. Recent generative adversarial networks (GANs) can achieve excellent results …