# Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution

arXiv: https://arxiv.org/abs/2405.04964 · HTML: https://mlsanity.com/paper/2405.04964/

## Key facts

- Cited by 48 papers in the map (data through 14 Oct 2026).
- Placed in Point clouds, detection and remote sensing, one of 10 directions in State-space sequence models (S4, Mamba).
- Builds on 46 of its 80 references that are in the map.
- First posted on arXiv 8 May 2024.

## Placed in

- State-space sequence models (S4, Mamba) / [Point clouds, detection and remote sensing](https://mlsanity.com/ssm/point-clouds-detection-and-remote-sensing/)

## Builds on (most cited first, 30 of 46)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://mlsanity.com/paper/2312.00752/) (2023)
- [Efficiently Modeling Long Sequences with Structured State Spaces](https://mlsanity.com/paper/2111.00396/) (2021)
- [Enhanced Deep Residual Networks for Single Image Super-Resolution](https://mlsanity.com/paper/1707.02921/) (2017)
- [Image Super-Resolution Using Very Deep Residual Channel Attention Networks](https://mlsanity.com/paper/1807.02758/) (2018)
- [Image Super-Resolution Using Deep Convolutional Networks](https://mlsanity.com/paper/1501.00092/) (2014)
- [VMamba: Visual State Space Model](https://mlsanity.com/paper/2401.10166/) (2024)
- [Accurate Image Super-Resolution Using Very Deep Convolutional Networks](https://mlsanity.com/paper/1511.04587/) (2015)
- [Residual Dense Network for Image Super-Resolution](https://mlsanity.com/paper/1802.08797/) (2018)
- [Simplified State Space Layers for Sequence Modeling](https://mlsanity.com/paper/2208.04933/) (2022)
- [A Survey on Visual Transformer](https://mlsanity.com/paper/2012.12556/) (2020)
- [DOTA: A Large-scale Dataset for Object Detection in Aerial Images](https://mlsanity.com/paper/1711.10398/) (2017)
- [Understanding the Effective Receptive Field in Deep Convolutional Neural Networks](https://mlsanity.com/paper/1701.04128/) (2017)
- [FDA: Fourier Domain Adaptation for Semantic Segmentation](https://mlsanity.com/paper/2004.05498/) (2020)
- [Activating More Pixels in Image Super-Resolution Transformer](https://mlsanity.com/paper/2205.04437/) (2022)
- [U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation](https://mlsanity.com/paper/2401.04722/) (2024)
- [MambaIR: A Simple Baseline for Image Restoration with State-Space Model](https://mlsanity.com/paper/2402.15648/) (2024)
- [AID: A Benchmark Dataset for Performance Evaluation of Aerial Scene Classification](https://mlsanity.com/paper/1608.05167/) (2016)
- [Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark](https://mlsanity.com/paper/1909.00133/) (2019)
- [Rethinking Coarse-to-Fine Approach in Single Image Deblurring](https://mlsanity.com/paper/2108.05054/) (2021)
- [A Fourier-based Framework for Domain Generalization](https://mlsanity.com/paper/2105.11120/) (2021)
- [Single Image Super-Resolution via a Holistic Attention Network](https://mlsanity.com/paper/2008.08767/) (2020)
- [Visual Attention Network](https://mlsanity.com/paper/2202.09741/) (2022)
- [Learning A Sparse Transformer Network for Effective Image Deraining](https://mlsanity.com/paper/2303.11950/) (2023)
- [Efficient and Explicit Modelling of Image Hierarchies for Image Restoration](https://mlsanity.com/paper/2303.00748/) (2023)
- [Interpreting Super-Resolution Networks with Local Attribution Maps](https://mlsanity.com/paper/2011.11036/) (2020)
- [ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model](https://mlsanity.com/paper/2404.03425/) (2024)
- [Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement](https://mlsanity.com/paper/2302.11831/) (2023)
- [Fusion-Mamba for Cross-modality Object Detection](https://mlsanity.com/paper/2404.09146/) (2024)

## Built on by (most cited first, 30 of 48)

- [The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report](https://mlsanity.com/paper/2604.03198/) (2026)
- [Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution](https://mlsanity.com/paper/2410.10140/) (2024)
- [Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection](https://mlsanity.com/paper/2406.06949/) (2024)
- [Multi-Scale Direction-Aware Network for Infrared Small Target Detection](https://mlsanity.com/paper/2406.02037/) (2024)
- [MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling](https://mlsanity.com/paper/2408.10854/) (2024)
- [S3Mamba: Arbitrary-Scale Super-Resolution via Scaleable State Space Model](https://mlsanity.com/paper/2411.11906/) (2024)
- [NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study](https://mlsanity.com/paper/2504.15003/) (2025)
- [Dual-domain Modulation Network for Lightweight Image Super-Resolution](https://mlsanity.com/paper/2503.10047/) (2025)
- [Advancing Image Super-resolution Techniques in Remote Sensing: A Comprehensive Survey](https://mlsanity.com/paper/2505.23248/) (2025)
- [Dual Selective Fusion Transformer Network for Hyperspectral Image Classification](https://mlsanity.com/paper/2410.03171/) (2024)
- [RemoteDet-Mamba: A Hybrid Mamba-CNN Network for Multi-modal Object Detection in Remote Sensing Images](https://mlsanity.com/paper/2410.13532/) (2024)
- [Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS Demosaicing](https://mlsanity.com/paper/2503.16134/) (2025)
- [Dual-Branch Remote Sensing Infrared Image Super-Resolution](https://mlsanity.com/paper/2604.10112/) (2026)
- [Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks](https://mlsanity.com/paper/2503.04223/) (2025)
- [Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook](https://mlsanity.com/paper/2505.00630/) (2025)
- [One-Step Diffusion-based Real-World Image Super-Resolution with Visual Perception Distillation](https://mlsanity.com/paper/2506.02605/) (2025)
- [Latent Diffusion, Implicit Amplification: Efficient Continuous-Scale Super-Resolution for Remote Sensing Images](https://mlsanity.com/paper/2410.22830/) (2024)
- [HSRMamba: Contextual Spatial-Spectral State Space Model for Single Image Hyperspectral Super-Resolution](https://mlsanity.com/paper/2501.18500/) (2025)
- [MambaMoE: Mixture-of-Spectral-Spatial-Experts State Space Model for Hyperspectral Image Classification](https://mlsanity.com/paper/2504.20509/) (2025)
- [SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language Model](https://mlsanity.com/paper/2505.23010/) (2025)
- [Guidance Disentanglement Network for Optics-Guided Thermal UAV Image Super-Resolution](https://mlsanity.com/paper/2410.20466/) (2024)
- [Marine Saliency Segmenter: Object-Focused Conditional Diffusion with Region-Level Semantic Knowledge Distillation](https://mlsanity.com/paper/2504.02391/) (2025)
- [PAD: Phase-Amplitude Decoupling Fusion for Multi-Modal Land Cover Classification](https://mlsanity.com/paper/2504.19136/) (2025)
- [Diffusion Models for Hyperspectral Image Analysis: A Comprehensive Review](https://mlsanity.com/paper/2505.11158/) (2025)
- [Lightweight Quad Bayer HybridEVS Demosaicing via State Space Augmented Cross-Attention](https://mlsanity.com/paper/2508.06058/) (2025)
- [ME-Mamba: Multi-Expert Mamba with Efficient Knowledge Capture and Fusion for Multimodal Survival Analysis](https://mlsanity.com/paper/2509.16900/) (2025)
- [Wavelet-Assisted Mamba for Satellite-Derived Sea Surface Temperature Super-Resolution](https://mlsanity.com/paper/2509.24334/) (2025)
- [All-in-One Video Restoration under Smoothly Evolving Unknown Weather Degradations](https://mlsanity.com/paper/2601.00533/) (2026)
- [FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution](https://mlsanity.com/paper/2506.14121/) (2025)
- [MSF-Mamba: Motion-aware State Fusion Mamba for Efficient Micro-Gesture Recognition](https://mlsanity.com/paper/2510.10478/) (2025)

## Abstract (arXiv)

Recent progress in remote sensing image (RSI) super-resolution (SR) has exhibited remarkable performance using deep neural networks, e.g., Convolutional Neural Networks and Transformers. However, existing SR methods often suffer from either a limited receptive field or quadratic computational overhead, resulting in sub-optimal global representation and unacceptable computational costs in large-scale RSI. To alleviate these issues, we develop the first attempt to integrate the Vision State Space Model (Mamba) for RSI-SR, which specializes in processing large-scale RSI by capturing long-range dependency with linear complexity. To achieve better SR reconstruction, building upon Mamba, we devise a Frequency-assisted Mamba framework, dubbed FMSR, to explore the spatial and frequent correlations. In particular, our FMSR features a multi-level fusion architecture equipped with the Frequency Selection Module (FSM), Vision State Space Module (VSSM), and Hybrid Gate Module (HGM) to grasp their merits for effective spatial-frequency fusion. Considering that global and local dependencies are complementary and both beneficial for SR, we further recalibrate these multi-level features for accurate feature fusion via learnable scaling adaptors. Extensive experiments on AID, DOTA, and DIOR benchmarks demonstrate that our FMSR outperforms state-of-the-art Transformer-based methods HAT-L in terms of PSNR by 0.11 dB on average, while consuming only 28.05% and 19.08% of its memory consumption and complexity, respectively. Code will be available at https://github.com/XY-boy/FreMamba