Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
[PDF][PDF] A comprehensive review of deep learning-based single image super-resolution
SMA Bashir, Y Wang, M Khan, Y Niu - PeerJ Computer Science, 2021 - peerj.com
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 …
resolution of an image in the field of computer vision. In the last two decades, significant …
From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution
Over the past few years, single image super-resolution (SR) has become a hotspot in the
remote sensing area, and numerous methods have made remarkable progress in this …
remote sensing area, and numerous methods have made remarkable progress in this …
Deep learning for image super-resolution: A survey
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 …
enhance the resolution of images and videos in computer vision. Recent years have …
Blind image super-resolution: A survey and beyond
Blind image super-resolution (SR), aiming to super-resolve low-resolution images with
unknown degradation, has attracted increasing attention due to its significance in promoting …
unknown degradation, has attracted increasing attention due to its significance in promoting …
Real-world super-resolution via kernel estimation and noise injection
Recent state-of-the-art super-resolution methods have achieved impressive performance on
ideal datasets regardless of blur and noise. However, these methods always fail in real …
ideal datasets regardless of blur and noise. However, these methods always fail in real …
Toward real-world single image super-resolution: A new benchmark and a new model
Most of the existing learning-based single image super-resolution (SISR) methods are
trained and evaluated on simulated datasets, where the low-resolution (LR) images are …
trained and evaluated on simulated datasets, where the low-resolution (LR) images are …
Component divide-and-conquer for real-world image super-resolution
In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset,
ie, DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the …
ie, DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the …
Frequency separation for real-world super-resolution
Most of the recent literature on image super-resolution (SR) assumes the availability of
training data in the form of paired low resolution (LR) and high resolution (HR) images or the …
training data in the form of paired low resolution (LR) and high resolution (HR) images or the …
A review of image super-resolution approaches based on deep learning and applications in remote sensing
At present, with the advance of satellite image processing technology, remote sensing
images are becoming more widely used in real scenes. However, due to the limitations of …
images are becoming more widely used in real scenes. However, due to the limitations of …