MRA-IDN: A Lightweight Super-Resolution Framework of Remote Sensing Images Based on Multiscale Residual Attention Fusion Mechanism

MRA-IDN: A Lightweight Super-Resolution Framework of Remote Sensing Images Based on Multiscale Residual Attention Fusion Mechanism

The emergence of deep-learning technology has significantly improved the performance of super-resolution algorithms for a single remote sensing image; however, the number of deep-learning model parameters is large, which limits its real-time deployment. In addition, the reconstructed image quality s...

Full description

Bibliographic Details
Main Authors: Wujian Ye, Bili Lin, Junming Lao, Yijun Liu, Zhenyi Lin
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep neural network (DNN)
high- and low-frequency (LF) reconstruction
high-frequency (HF) attention
multiscale features
remote sensing super-resolution
Online Access:https://ieeexplore.ieee.org/document/10480122/

Internet

https://ieeexplore.ieee.org/document/10480122/

Similar Items