Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion

Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion

Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. Previously, convolutional neural network (CNN) achieves impressive progress in SISR due to its strong local feature extrac...

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Bibliographic Details
Main Authors: Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
multiscale learning
remote sensing images
superresolution (SR)
Transformer
Online Access:https://ieeexplore.ieee.org/document/10764782/
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https://ieeexplore.ieee.org/document/10764782/

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