Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion-Based Transformer Network for Remote Sensing Image Super-Resolution-Reference-Cited by-同舟云学术

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Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion-Based Transformer Network for Remote Sensing Image Super-Resolution

Published:2023 Issue: Volume:61 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Lu Yuting¹,Min Lingtong²^ORCID,Wang Binglu³^ORCID,Zheng Le³^ORCID,Wang Xiaoxu¹^ORCID,Zhao Yongqiang¹^ORCID,Yang Le¹^ORCID,Long Teng³

Affiliation:

1. School of Automation, Northwestern Polytechnical University, Xi’an, China

2. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China

3. Radar Research Laboratory, School of Information and Electronics, Beijing Institute of Technology, Beijing, China

Funder

Postdoctoral Science Foundation of China

Fourth Special Grant of China Postdoctoral Science Foundation

Shaanxi Science Fund for Distinguished Young Scholars

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10323091.pdf?arnumber=10323091

Reference80 articles.

1. A Review of Image Super-Resolution Approaches Based on Deep Learning and Applications in Remote Sensing

2. Super-Resolution for Remote Sensing Images via Local–Global Combined Network

3. Cascade Scale-Aware Distillation Network for Lightweight Remote Sensing Image Super-Resolution

4. Enhanced Deep Residual Networks for Single Image Super-Resolution

5. Multiscale Dual-Domain Guidance Network for Pan-Sharpening

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Two-Stage Spatial-Frequency Joint Learning for Large-Factor Remote Sensing Image Super-Resolution;IEEE Transactions on Geoscience and Remote Sensing;2024

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