Here I mainly list the deep learning-based remote sensing image super-resolution methods.
| ID | Year | Title | Model | Published | Code | Keywords |
|---|---|---|---|---|---|---|
| [1] | 2017 | Super-Resolution for Remote Sensing Images via Local–Global Combined Network | LGCNet | IEEE GRSL | - | SISR, multi-scale features |
| [2] | 2017 | Video Satellite Imagery Super Resolution via Convolutional Neural Networks | - | IEEE GRSL | - | Video SR |
| [3] | 2018 | A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution | - | IEEE TGRS | - | Unsupervised SR |
| [4] | 2018 | Deep Distillation Recursive Network for Remote Sensing Imagery Super-Resolution | DDRN | RS | - | - |
| [5] | 2018 | Aerial Image Super Resolution via Wavelet Multiscale Convolutional Neural Networks | WMCNN | IEEE GRSL | - | SISR, Wavelet decomposition |
| [6] | 2020 | Coupled Adversarial Training for Remote Sensing Image Super-Resolution | CDGAN | IEEE TGRS | - | SISR, GAN, coupled discrimator |
| [7] | 2020 | A Unified Network for Arbitrary Scale Super-Resolution of Video Satellite Images | ASSR | IEEE TGRS | - | Video SR, arbitrary scale, 3D conv |
| [8] | 2021 | Hybrid-Scale Self-Similarity Exploitation for Remote Sensing Image Super-Resolution | HSENet | IEEE TGRS | code | SISR, non-local, hybrid-scale self-similarity |
| [9] | 2021 | Deep-Learning-Based Super-Resolution of Video Satellite Imagery by the Coupling of Multiframe and Single-Frame Models | EGVSR | IEEE TGRS | - | Video SR, edge-guided |
| [10] | 2021 | RRSGAN: Reference-Based Super-Resolution for Remote Sensing Image | RRSGAN | IEEE TGRS | code | RefSR, GAN |
| [11] | 2021 | Collaborative Network for Super-Resolution and Semantic Segmentation of Remote Sensing Images | ColNet | IEEE TGRS | - | SISR, multi-task learning, semantic segmentation |
| [12] | 2021 | Satellite Video Super-Resolution via Multiscale Deformable Convolution Alignment and Temporal Grouping Projection | - | IEEE TGRS | - | Video SR |
| [13] | 2021 | Single-Image Super-Resolution for Remote Sensing Images Using a Deep Generative Adversarial Network With Local and Global Attention Mechanisms | - | IEEE TGRS | - | SISR, GAN, attention |
| [14] | 2021 | Target-Guided Feature Super-Resolution for Vehicle Detection in Remote Sensing Images | - | IEEE GRSL | - | feature SR, multi-task |
| [15] | 2021 | Hierarchical Feature Aggregation and Self-Learning Network for Remote Sensing Image Continuous-Scale Super-Resolution | RSI-HFAS | IEEE GRSL | code | SISR, arbitrary scale, hierarchical feature |
| [16] | 2021 | Remote Sensing Image Super-Resolution via Residual Aggregation and Split Attentional Fusion Network | RASAF | IEEE JSTAR | - | SISR, split attention |
| [17] | 2021 | ESPC_NASUnet: An End-to-End Super-Resolution Semantic Segmentation Network for Mapping Buildings From Remote Sensing Images | ESPC-NASUnet | IEEE JSTAR | - | multi-task |
| [18] | 2022 | Transformer-based Multi-Stage Enhancement for Remote Sensing Image Super-Resolution | TransENet | IEEE TGRS | code | SISR, transformer, multi-stage |
| [19] | 2022 | Real-world remote sensing image super-resolution via a practical degradation model and a kernel-aware network | - | ISPRS | - | RealSR, VAE, kernel prediction, kernel-aware network |
| [20] | 2022 | Large-factor Super-resolution of Remote Sensing Images with Spectra-guided Generative Adversarial Networks | SpecGAN | IEEE TGRS | code | Large-scale SR, Spectra-guided, GAN |
| [21] | 2022 | FeNet: Feature Enhancement Network for Lightweight Remote-Sensing Image Super-Resolution | - | IEEE TGRS | code | Lightweight SR |
| [22] | 2022 | Multiattention Generative Adversarial Network for Remote Sensing Image Super-Resolution | - | IEEE TGRS | - | SISR, GAN, multi-attention |
| [23] | 2022 | A Deep Multitask Convolutional Neural Network for Remote Sensing Image Super-Resolution and Colorization | - | IEEE TGRS | - | multi-task |
| [24] | 2022 | Dual Learning-Based Graph Neural Network for Remote Sensing Image Super-Resolution | - | IEEE TGRS | code | SISR |
| [25] | 2022 | From Artifact Removal to Super-Resolution | - | IEEE TGRS | - | - |
| [26] | 2022 | Multilayer Degradation Representation-Guided Blind Super-Resolution for Remote Sensing Images | - | IEEE TGRS | code | Blind SR |
| [27] | 2022 | Deep Joint Estimation Network for Satellite Video Super-Resolution With Multiple Degradations | - | IEEE TGRS | - | Video SR, Blind SR |
| [28] | 2022 | Contextual Transformation Network for Lightweight Remote-Sensing Image Super-Resolution | - | IEEE TGRS | code | Lightweight SR |
| [29] | 2022 | Remote Sensing Image Super-Resolution via Dual-Resolution Network Based on Connected Attention Mechanism | - | IEEE TGRS | - | SISR, connected attention |
| [30] | 2022 | Multiframe Video Satellite Image Super-Resolution via Attention-Based Residual Learning | - | IEEE TGRS | - | Video SR, attention |
| [31] | 2022 | SWCGAN: Generative Adversarial Network Combining Swin Transformer and CNN for Remote Sensing Image Super-Resolution | SWCGAN | IEEE JSTAR | - | GAN, swin transformer |
| [32] | 2023 | Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing Strategy | SalDRN | IEEE TGRS | code | Lightweight SR, saliency, dynamic routing |
| [33] | 2023 | A CNN-Based Sentinel-2 Image Super-Resolution Method Using Multiobjective Training | - | IEEE TGRS | - | SISR |
| [34] | 2023 | Learning Dynamic Scale Awareness and Global Implicit Functions for Continuous-Scale Super-Resolution of Remote Sensing Images | SADN | IEEE TGRS | code | SISR, continuous-scale, implicit function |
| [35] | 2023 | Continuous Remote Sensing Image Super-Resolution Based on Context Interaction in Implicit Function Space | FunSR | IEEE TGRS | code | SISR, continuous-scale, implicit function, context interaction |
| [36] | 2023 | Hybrid Attention-Based U-Shaped Network for Remote Sensing Image Super-Resolution | HAUNet | IEEE TGRS | code | SISR, hybrid attention |
| [37] | 2023 | Deep Blind Super-Resolution for Satellite Video | - | IEEE TGRS | code | Video SR, blind SR |
| [38] | 2023 | A Progressive Feature Enhancement Deep Network for Large-Scale Remote Sensing Image Superresolution | - | IEEE TGRS | - | Large-scale SR, progressive feature enhancement |
| [39] | 2023 | Enhancing Remote Sensing Image Super-Resolution with Efficient Hybrid Conditional Diffusion Model | - | RS | - | SISR, diffusion model |
| [40] | 2023 | Hybrid-Scale Hierarchical Transformer for Remote Sensing Image Super-Resolution | - | RS | - | SISR, transformer, hybrid-scale |
| [41] | 2023 | Remote Sensing Image Super-Resolution With Residual Split Attention Mechanism | - | IEEE JSTARS | - | SISR, split attention |
| [42] | 2023 | AEFormer: Zoom Camera Enables Remote Sensing Super-Resolution via Aligned and Enhanced Attention | AEFormer | RS | - | zoom camera, reference-based sr |
| [43] | 2023 | From Degrade to Upgrade Learning a Self-Supervised Degradation-Guided Adaptive Network for Blind Remote Sensing Image Super-Resolution | DRSR | Information Fusion | code | blind SR, self-supervised |
| [44] | 2023 | Zooming Out on Zooming In: Advancing Super-Resolution for Remote Sensing | - | arXiv | code | new metric CLIPSCORE, new dataset S2-NAIP |
| [45] | 2023 | Multi-frame super-resolution of remote sensing images using attention-based GAN models | - | Knowledge-Based Systems | - | - |
| [46] | 2023 | Cross-sensor remote sensing imagery super-resolution via an edge-guided attention-based network | EGASR | ISPRS | code | real-world, cross-sensor, edge-guided |
| [47] | 2023 | CLSR: Contrastive Learning for Semi-Supervised Remote Sensing Image Super-Resolution | CLSR | IEEE GRSL | - | - |
| [48] | 2024 | Two-Stage Spatial-Frequency Joint Learning for Large-Factor Remote Sensing Image Super-Resolution | TSFNet | IEEE TGRS | code | - |
| [49] | 2024 | TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution | TTST | IEEE TIP | code | sparse Transformer |
| [50] | 2024 | Local-Global Context-Aware Generative Dual-Region Adversarial Networks for Remote Sensing Scene Image Super-Resolution | LGCGDAN | IEEE TGRS | - | - |
| [51] | 2024 | MSWAGAN: Multispectral Remote Sensing Image Super-Resolution Based on Multiscale Window Attention Transformer | MSWAGAN | IEEE TGRS | - | - |
| [52] | 2024 | CSwT-SR: Conv-Swin Transformer for Blind Remote Sensing Image Super-Resolution With Amplitude-Phase Learning and Structural Detail Alternating Learning | CSwT-SR | IEEE TGRS | - | - |
| [53] | 2024 | GCRDN: Global Context-Driven Residual Dense Network for Remote Sensing Image Superresolution | GCRDN | IEEE JSTARS | code | - |
| [54] | 2024 | Multiscale Residual Dense Network for the Super-Resolution of Remote Sensing Images | MRDN | IEEE TGRS | - | - |
| [55] | 2024 | EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution | EDiffSR | IEEE TGRS | code | - |
| [56] | 2024 | Building Bridges across Spatial and Temporal Resolutions Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model | RefDiff | CVPR | code | - |
| [57] | 2024 | Non-Local Similarity-Based Attentive Graph Convolution Network for Remote Sensing Image Super-Resolution | NSGCN | IEEE TGRS | code | - |
| [58] | 2024 | Semantic Guided Large Scale Factor Remote Sensing Image Super-resolution with Generative Diffusion Prior | SGDM | ISPRS | code | reference-based sr |
| [59] | 2024 | Scale-Aware Backprojection Transformer for Single Remote Sensing Image Super-Resolution | - | IEEE TGRS | - | - |
| [60] | 2024 | Hyper-Laplacian Prior for Remote Sensing Image Super-Resolution | - | IEEE TGRS | - | - |
| [61] | 2024 | Efficient Swin Transformer for Remote Sensing Image Super-Resolution | ESTNet | IEEE TIP | code | - |
| [62] | 2024 | ACT-SR: Aggregation Connection Transformer for Remote Sensing Image Super-Resolution | ACT-SR | IEEE JSTARS | code | - |
| [63] | 2024 | DRGAN: A Detail Recovery-Based Model for Optical Remote Sensing Images Super-Resolution | DRGAN | IEEE TGRS | - | GAN-bassed method |
| [64] | 2024 | DTESR: Remote Sensing Imagery Super-Resolution With Dynamic Reference Textures Exploitation | DTESR | IEEE GRSL | - | reference-based sr |
| [65] | 2024 | Toward Real-World Remote Sensing Image Super-Resolution: A New Benchmark and an Efficient Model | - | IEEE TGRS | - | Real-world sr, dataset |
| [66] | 2024 | Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution | FMSR | IEEE TMM | code | Mamba |
| [67] | 2025 | Binary Lightweight Neural Networks for Arbitrary Scale Super-Resolution of Remote Sensing Images | BLiSR | IEEE TGRS | - | Lightweight sr, arbitrary scale |
| [68] | 2025 | NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator Diffusion | NeurOp-Diff | arXiv | - | diffusion |
| [69] | 2025 | Unsupervised Image Super-Resolution for High-Resolution Satellite Imagery via Omnidirectional Real-to-Synthetic Domain Translation | IEEE JSTARS | - | unsupervised, real-world sr | |
| [70] | 2025 | Super-Resolution for Remote Sensing Imagery via the Coupling of a Variational Model and Deep Learning | - | IEEE TGRS | - | multiframe SR, model-based |
| [71] | 2025 | Semantic-aware Guidance for Blind Super-resolution of Remote Sensing Images | - | IEEE GRSL | - | blind SR |
| [72] | 2025 | CSCT: Channel-Spatial Coherent Transformer for Remote Sensing Image Super-Resolution | CSCT | IEEE TGRS | - | - |
| [73] | 2025 | Dual-Domain Optimization Model Based on Discrete Fourier Transform and Frequency-Domain Fusion for Remote Sensing Single-Image Super-Resolution | - | IEEE TGRS | code | - |
| [74] | 2025 | Heterogeneous Mixture of Experts for Remote Sensing Image Super-Resolution | - | arXiv | code | - |
| [75] | 2025 | SCAT: Shift Channel Attention Transformer for Remote Sensing Image Super-Resolution | SCAT | IEEE JSTARS | - | - |
| [76] | 2025 | HyDA-Net: A Hybrid Dense Attention Network for Remote Sensing Multi-Image Super-Resolution | HyDA-Net | IEEE JSTARS | - | multi-image SR |
| [77] | 2025 | Rethinking Dual-Stream Super-Resolution for Enhancing Remote Sensing Object Detection | - | ICASSP | - | SR with high-level task |
If you find this repository helpful in your research, please kindly consider citing our works on this topic, such as LGCNet, HSENet, TranSENet, CDGAN, FunSR, and SpecGAN.
For more questions and suggestions, feel free to contact me :)
Email: [email protected], [email protected]