LSTMConvSR: Joint Long–Short-Range Modeling via LSTM-First–CNN-Next Architecture for Remote Sensing Image Super-Resolution

LSTMConvSR: Joint Long–Short-Range Modeling via LSTM-First–CNN-Next Architecture for Remote Sensing Image Super-Resolution

The inability of existing super-resolution methods to jointly model short-range and long-range spatial dependencies in remote sensing imagery limits reconstruction efficacy. To address this, we propose LSTMConvSR, a novel framework inspired by top-down neural attention mechanisms. Our approach pione...

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Bibliographic Details
Main Authors: Qiwei Zhu, Guojing Zhang, Xiaoying Wang, Jianqiang Huang
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Remote Sensing
Subjects:
remote sensing
super-resolution
top-down neural attention
LSTM-first–CNN-next
Online Access:https://www.mdpi.com/2072-4292/17/15/2745
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https://www.mdpi.com/2072-4292/17/15/2745

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