A Lightweight CNN-Transformer Implemented via Structural Re-Parameterization and Hybrid Attention for Remote Sensing Image Super-Resolution

A Lightweight CNN-Transformer Implemented via Structural Re-Parameterization and Hybrid Attention for Remote Sensing Image Super-Resolution

Remote sensing imagery contains rich information about geographical targets, and performing super-resolution (SR) reconstruction on such images requires greater feature representation capabilities. Convolutional neural network (CNN)-based methods excel at extracting intricate local features but fall...

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Bibliographic Details
Main Authors: Jie Wang, Hongwei Li, Yifan Li, Zilong Qin
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:ISPRS International Journal of Geo-Information
Subjects:
super-resolution
remote sensing
CNN-Transformer
lightweight
hybrid attention
Online Access:https://www.mdpi.com/2220-9964/14/1/8
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