光学精密工程2026，Vol.34Issue(9)：1468-1495,28.DOI:10.37188/OPE.20263409.1468
基于Mamba架构的遥感图像超分辨率重建方法综述
Review of Mamba-based methods for remote sensing image super-resolution
摘要
Abstract
The visual architecture Mamba,built on selective state-space models,enables long-range de-pendencies to be modeled with linear complexity through selective scanning and state updating,providing a promising approach for balancing global representation learning and computational efficiency in remote sensing image super-resolution.This paper systematically reviews the theoretical foundations and method-ological framework of Mamba-based super-resolution,summarizes representative studies,and categorizes them into four major directions:frequency-domain modeling and spectral enhancement,structural fusion and attention enhancement,cross-modal and multi-source modeling,and lightweight design with re-param-eterization.Under a unified synthetic degradation evaluation protocol,representative methods are compar-atively analyzed in terms of reconstruction performance,perceptual quality,and applicability on bench-mark datasets,including AID,DIOR,and UCAS_AOD.The results demonstrate that Mamba-based methods exhibit substantial potential for preserving structural continuity,restoring geometric consistency,and suppressing pseudo-textures,while achieving competitive reconstruction performance across multiple datasets.Finally,key challenges and future trends,including real-world degradations,cross-domain gen-eralization,and reproducible benchmarks,are discussed,providing valuable references for future research and practical deployment.关键词
遥感图像/超分辨率重建/视觉状态空间模型/Mamba/频域增强/跨模态融合/轻量化Key words
remote sensing images/super-resolution reconstruction/visual state space models/Mamba/frequency domain enhancement/cross-modal fusion/lightweight分类
信息技术与安全科学引用本文复制引用
李秉豪,姜肖楠,傅瑶,王亚楠,万龙腾,吴凡路..基于Mamba架构的遥感图像超分辨率重建方法综述[J].光学精密工程,2026,34(9):1468-1495,28.基金项目
国家自然科学基金面上项目(No.62371352) （No.62371352）
国家重点研发计划资助项目(No.2022YFB3902300) （No.2022YFB3902300）
