Ntire 2020 challenge on real-world image super-resolution: Methods and results

A Lugmayr, M Danelljan… - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on
the participating methods and final results. The challenge addresses the real world setting …

Deep learning in medical image super resolution: a review

H Yang, Z Wang, X Liu, C Li, J Xin, Z Wang - Applied Intelligence, 2023 - Springer
Super-resolution (SR) reconstruction is a hot topic in medical image processing. SR implies
reconstructing corresponding high-resolution (HR) images from observed low-resolution …

COLA-Net: Collaborative attention network for image restoration

C Mou, J Zhang, X Fan, H Liu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Local and non-local attention-based methods have been well studied in various image
restoration tasks while leading to promising performance. However, most of the existing …

PGMAN: An unsupervised generative multiadversarial network for pansharpening

H Zhou, Q Liu, Y Wang - IEEE Journal of Selected Topics in …, 2021 - ieeexplore.ieee.org
Pansharpening aims at fusing a low-resolution multispectral (MS) image and a high-
resolution (HR) panchromatic (PAN) image acquired by a satellite to generate an HR MS …

Unsupervised cycle-consistent generative adversarial networks for pan sharpening

H Zhou, Q Liu, D Weng, Y Wang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Deep learning-based pan sharpening has received significant research interest in recent
years. Most of the existing methods fall into the supervised learning framework in which they …

Implementation of super resolution in images based on generative Adversarial network

KS Reddy, VP Vijayan, AD Gupta… - … on Smart Structures …, 2022 - ieeexplore.ieee.org
A 3D visualization of a microscopic object is provided by the integral imaging microscopy
system. A generative-adversarial-network (GAN) relied on super resolution (SR) algorithm is …

Deep learning-based super-resolution for harmful algal bloom monitoring of inland water

DH Kwon, SM Hong, A Abbas, S Park… - GIScience & Remote …, 2023 - Taylor & Francis
Inland water frequently occurs during harmful algal blooms (HABs), rendering it challenging
to comprehend the spatiotemporal features of algal dynamics. Recently, remote sensing has …

A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges

M Megahed, A Mohammed - Wiley Interdisciplinary Reviews …, 2024 - Wiley Online Library
In machine learning, a generative model is responsible for generating new samples of data
in terms of a probabilistic model. Generative adversarial network (GAN) has been widely …

Direct unsupervised super-resolution using generative adversarial network (DUS-GAN) for real-world data

K Prajapati, V Chudasama, H Patel… - … on Image Processing, 2021 - ieeexplore.ieee.org
The deep learning models for the Single Image Super-Resolution (SISR) task have found
success in recent years. However, one of the prime limitations of existing deep learning …

Ultrasound speckle reduction using wavelet-based generative adversarial network

HG Khor, G Ning, X Zhang… - IEEE Journal of Biomedical …, 2022 - ieeexplore.ieee.org
The visual quality of ultrasound (US) images is crucial for clinical diagnosis and treatment.
The main source of image quality degradation is the inherent speckle noise generated …