NGSTGAN: N-Gram Swin Transformer and Multi-Attention U-Net Discriminator for Efficient Multi-Spectral Remote Sensing Image Super-Resolution

NGSTGAN: N-Gram Swin Transformer and Multi-Attention U-Net Discriminator for Efficient Multi-Spectral Remote Sensing Image Super-Resolution

The reconstruction of high-resolution (HR) remote sensing images (RSIs) from low-resolution (LR) counterparts is a critical task in remote sensing image super-resolution (RSISR). Recent advancements in convolutional neural networks (CNNs) and Transformers have significantly improved RSISR performanc...

Full description

Saved in:
Bibliographic Details
Main Authors: Chao Zhan, Chunyang Wang, Bibo Lu, Wei Yang, Xian Zhang, Gaige Wang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
super-resolution
deep learning
convolutional neural network
generative adversarial networks
transformer
N-Gram
Online Access:https://www.mdpi.com/2072-4292/17/12/2079
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items