Remote Sensing Image Super-Resolution

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Remote sensing image super-resolution estimates finer spatial detail from coarse satellite or aerial imagery, supporting mapping, environmental monitoring, and object detection. Methods range from CNNs and transformers to GANs, diffusion and flow models, often using multispectral bands, temporal imagery, sensor physics, or self-supervised learning when high-resolution ground truth is scarce. Pansharpening, hyperspectral and SAR reconstruction, and task-specific downscaling address different sensors and applications. A central challenge is balancing visual detail with physical and radiometric fidelity: generated textures can be plausible but inaccurate, synthetic training may not transfer to real sensors, and standard image metrics do not always predict downstream task performance.

Latest papers

35 papers3 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

From Sentinel-2 to 1-m Imagery: Real-World $\times 10$ Cross-Sensor Super-Resolution via Visual Autoregressive Modeling
Oct 26, 2026Tailai Chen, Yuluxin Fu, Jie Deng +3Remote Sensing Image Super-Resolution Image Super-Resolution
College of Water Resources and Intelligence Engineering, China Agricultural University, Beijing 100083, China · College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China · Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China +4
MultiAltitudeSR: Multi-Altitude Agricultural UAV Image Super-Resolution via Physical Ground Sampling Distance Conditioning
Oct 18, 2026Xintong Jiang, Yu Tian, Yixue Liu +3Image Super-Resolution Remote Sensing Image Super-Resolution
Department of Bioresource Engineering, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, H9X 3V9, Quebec, Canada · Michigan State University, 426 Auditorium Road, East Lansing, 48824, Michigan, United States
MOSAIC: Multi-Scale Object-Centric Slot Adaptation with Image-Guided Prototype Conditioning for Remote Sensing Image Super-Resolution
Oct 9, 2026Liuqian Wang, Hanyu Xie, Rongzhen Zhao +6Remote Sensing Image Super-Resolution Object-Centric Representation Learning
Zhengzhou University, Henan, China · Aalto University, Finland · Beijing University of Technology, Beijing, China +1
Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data
Oct 5, 2026Hoàng-Ân Lê, Minh-Tan Pham, Solange Lemai-Chenevier +1Remote Sensing Image Segmentation Remote Sensing Image Super-Resolution
Universit´e Bretagne Sud, IRISA, UMR 6074, Vannes, France · Centre National d’Etudes Spatiales (CNES), Toulouse, France
AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution
Sep 7, 2026Yi-Chung Lai, Chin-Tien Wu, Yu-Chih ChenImage Deblurring Remote Sensing Image Super-Resolution
Institute of Mathematical Modeling and Scientific Computing National Yang Ming Chiao Tung University · Department of Computer Science National Yang Ming Chiao Tung University
ProSR: Semantic-Prototype-Guided Discrete Modeling for Physically Consistent SAR Super-Resolution
Sep 2, 2026Byoungwoo Kim, Munchurl KimRemote Sensing Image Super-Resolution
Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Deep Learning Super Resolution for Satellite Cloud Mask Downscaling
Aug 25, 2026Angelos Georgakis, Valentina Kanaki, Giorgos Giannopoulos +4Remote Sensing Remote Sensing Image Super-Resolution
BEYOND EO Centre, IAASARS, National Observatory of Athens, Athens, Greece · National and Kapodistrian University of Athens, Faculty of Physics, Section of Environmental Physics and Meteorology, Athens, Greece
Dual-Branch State-Displacement Network for Sea Surface Temperature Super-Resolution
Aug 15, 2026Wankun Chen, Feng Gao, Yanhai Gan +4Remote Sensing Image Super-Resolution
State Key Laboratory of Physical Oceanography, and also with the Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao 266100, China · State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Shandong Academy of Sciences, Qingdao 266100, China · Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762 USA
OGG-FR: Orthogonal Gradient Gaming and Frequency Rectification for Unmanned Aerial Vehicle Infrared Image Super-Resolution
Aug 10, 2026Yongsong Huang, Qingzhong Wang, Xiaofeng Liu +3Remote Sensing Image Super-Resolution Remote Sensing Infrared Image Super-Resolution
Tohoku University · Amazon Web Services · Yale University
RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery
Jul 15, 2026Tessa Cannon, Michel Tsamados, Petru Manescu +5Remote Sensing Image Super-Resolution Remote Sensing
Department of Computer Science, University College London · Department of Earth Sciences, University College London · Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany +1
Recovering Cloud Microstructures with Cascaded Diffusion Inversion
Jul 6, 2026Hanan Gani, Guy Pulik, Daniel Rosenfeld +2Diffusion Model Inversion Diffusion Models for Image Restoration
Mohamed Bin Zayed University of Artificial Intelligence · University of California, San Diego · Hebrew University of Jerusalem
Air Quality Downscaling with Station-Guided Pseudo-Supervision
Jul 6, 2026Guorun Wang, Simone Foti, Andreas D. Demou +5Remote Sensing Image Super-Resolution Air Quality Prediction
Imperial College London, UK · The Cyprus Institute, Cyprus · Northeastern University London, UK +1
Mind the Gap: Quantifying the Domain Gap in Cross-Sensor Diffusion Super-Resolution
Jun 26, 2026Dawid Kopeć, Katarzyna Jabłońska, Wojciech Kozłowski +1Synthetic-to-Real Domain Adaptation Diffusion Models for Image Restoration
WUST, Wybrzeże Stanisława Wyspiańskiego 27, 50-370 Wrocław, Poland · Tooploox, Tęczowa 7, 53-601 Wrocław, Poland
GSPan: A Continuous Gaussian Primitive Representation for Arbitrary-Scale Pansharpening
Jun 16, 2026Fangyi Li, Xiaoyuan Yang, Yixiao Li +3Remote Sensing Image Super-Resolution Remote Sensing
Beihang University, School of Mathematical Sciences, Beijing, 102206, China · Tsinghua University, Department of Automation, Beijing, 100084, China · National Research Council - Institute of Methodologies for Environmental Analysis, CNR-IMAA, Tito, 85050, Italy
NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts
Jun 7, 2026Yun-Hsuan Huang, Trong-An Bui, Chih-Hung ChuangOOD Generalization Remote Sensing Image Super-Resolution
Institute of Aerospace and Systems Engineering, National Taipei University of Technology, Taipei City, Taiwan.
Flow-based Gaussian Splatting for Continuous-Scale Remote Sensing Image Super-Resolution
May 21, 2026Jiangwei Mo, Xi Lu, Hanlin WuRemote Sensing Image Super-Resolution Image Super-Resolution
School of Information Science and Technology, Beijing Foreign Studies University, Beijing 100089, China
HyperBench: Standardizing and Scaling Synthetic Evaluation for Hyperspectral Super-Resolution
May 20, 2026Ritik Shah, Marco F. DuarteSynthetic Data Evaluation Remote Sensing Image Super-Resolution
University of Massachusetts Amherst, MA 01003
Learning to Balance: Decoupled Siamese Diffusion Transformer for Reference-Based Remote Sensing Image Super-Resolution
May 18, 2026Bin Luo, Runmin Dong, Zhaoyang Luo +4Diffusion Models for Image Restoration Diffusion Transformer
Tsinghua Shenzhen International Graduate School, Shenzhen, China · Sun Yat-sen University, Zhuhai, China · Tsinghua University, Beijing, China +1
Spatial-Frequency Gated Swin Transformer for Remote Sensing Single-Image Super-Resolution
May 10, 2026Md Aminur Hossain, Parekh Valkesh, Ayush V. Patel +3Remote Sensing Image Understanding Vision Transformer
Space Applications Centre, ISRO, Ahmedabad, India · New L J Institute of Engineering and Technology, Ahmedabad, India · Pandit Deendayal Energy University, Gandhinagar, India +2
Multispectral Blind Image Super-Resolution for Standing Dead Tree Segmentation
May 4, 2026Mete Ahishali, Anis Ur Rahman, Einari Heinaro +2Remote Sensing Image Segmentation Unsupervised Domain Adaptation
Department of Forest Sciences, University of Helsinki, Finland · CSC – IT Center for Science Ltd., Espoo, Finland · KOKO Forest Ltd. +1
SlimDiffSR: Toward Lightweight and Efficient Remote Sensing Image Super-Resolution via Diffusion Model Distillation
May 4, 2026Ce Wang, Zhenyu Hu, Wanjie SunDiffusion Model Distillation Remote Sensing Image Super-Resolution
School of Remote Sensing and Information Engineering, Wuhan University; Wuhan 430079, China
Flow matching for Sentinel-2 super-resolution: implementation, application, and implications
May 1, 2026Dakota Hester, Vitor S. Martins, Lucas B. Ferreira +2Flow Matching Land Cover Classification
Department of Agricultural and Biological Engineering, Mississippi State University · North Mississippi Research and Extension Center, Mississippi State University
Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
May 1, 2026Zhili Li, Kangyang Chai, Zhihao Wang +6Remote Sensing Image Super-Resolution Remote Sensing
University of Maryland · University of Pittsburgh · Worcester Polytechnic Institute +1
Edge-Cloud Collaborative Reconstruction via Structure-Aware Latent Diffusion for Downstream Remote Sensing Perception
Apr 28, 2026Yun Li, Xianju LiDiffusion Models for Image Restoration Edge Computing
School of Computer Science, China University of Geosciences, Wuhan, Hubei, China.
The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Apr 23, 2026Kai Liu, Haoyang Yue, Zeli Lin +65Remote Sensing Image Super-Resolution Remote Sensing Infrared Image Super-Resolution
Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images
Apr 19, 2026Hyam Omar Ali, Antoine Crosnier, Romain Abraham +3Self-Supervised Learning Remote Sensing Image Super-Resolution
Université d’Orléans, Université de Tours, CNRS, IDP, UMR 7013, Orléans, France · Faculty of Mathematical Sciences, University of Khartoum, Sudan · ENS Lyon, France +2
When Earth Foundation Models Meet Diffusion: An Application to Land Surface Temperature Super-Resolution
Apr 18, 2026Yiheng Chen, Zihui Ma, Peishi Jiang +6Diffusion Model Guidance Remote Sensing Image Super-Resolution
University of Alabama · Emory University · University of Michigan +2
Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework
Apr 15, 2026Enzhuo Zhang, Sijie Zhao, Dilxat Muhtar +3Remote Sensing Image Super-Resolution Image Super-Resolution
Nanjing University, China
Dual-Branch Remote Sensing Infrared Image Super-Resolution
Apr 11, 2026Xining Ge, Gengjia Chang, Weijun Yuan +6Remote Sensing Infrared Image Super-Resolution Image Super-Resolution
Hangzhou Dianzi University · Hefei University of Technology · Jinan University +1
Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints
Apr 10, 2026Zhiqi Yang, Jin-Liang Xiao, Shan Yin +2Pansharpening Multi-Source Image Fusion
University of Electronic Science and Technology of China, Chengdu, China · National Research Council, Institute of Methodologies for Environmental Analysis (CNR-IMAA), Tito, Italy

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From Sentinel-2 to 1-m Imagery: Real-World $\times 10$ Cross-Sensor Super-Resolution via Visual Autoregressive Modeling

Tailai Chen, Yuluxin Fu, Jie Deng, Shu Luo+2

College of Water Resources and Intelligence Engineering, China Agricultural University, Beijing 100083, China · College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China · Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China+4

Remote Sensing Image Super-Resolution Image Super-Resolution Autoregressive Image Super-Resolution

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Reconstructing 1-m imagery from Sentinel-2 combines two difficulties. The input and the reference are observed by different satellites, which differ in spatial resolution, spectral response, radiometry, acquisition time, and local geometry, so no synthetic degradation operator links them. The required magnification of ten in each spatial dimension also far exceeds the factors of two to four at which remote sensing super-resolution is usually developed. We study this real-world

\times 10

problem using YREB-SR, which pairs 2022 Sentinel-2 RGB composites with 2022 Jilin-1 RGB references resampled to a 1-m grid over the Yangtze River Economic Belt. The benchmark contains 11,559 geographically matched scene pairs, with 6,409, 2,135, and 3,015 assigned to training, validation, and testing, respectively. We develop CrossVAR, a visual autoregressive model that predicts the 1-m latent as a nine-scale hierarchy conditioned on the Sentinel-2 input and estimates the remaining quantization residual with a diffusion refiner run without injected noise. Complete 1600

\times

1600 scenes are reconstructed in overlapping windows that start on the Sentinel-2 pixel grid, as every training patch does, and every window is decoded at the size on which the decoder was trained before the windows are blended with Gaussian weights. On all 3,015 test scenes, CrossVAR achieves 27.60 dB PSNR, 0.7725 SSIM, 0.1451 LPIPS, and 7.15 FID, the best value of each metric among the compared methods. These results establish a strong autoregressive baseline for large-scale cross-sensor reconstruction. To facilitate reproducibility, the source code and implementation are publicly available at https://github.com/SHANOAL/RSSR.