SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL NETWORKS

61 citations as recorded by crossref.

1. Automatic Generation of Aerial Orthoimages Using Sentinel-2 Satellite Imagery with a Context-Based Deep Learning Approach S. Yoo et al. 10.3390/app11031089
2. A Prediction-to-Prediction Remote Sensing Image Super-Resolution Network under a Multi-Level Supervision Paradigm J. Guo et al. 10.3390/app132111827
3. Landsat-8 to Sentinel-2 Satellite Imagery Super-Resolution-Based Multiscale Dilated Transformer Generative Adversarial Networks C. Wang et al. 10.3390/rs15225272
4. Optically Enhanced Super-Resolution of Sea Surface Temperature Using Deep Learning D. Lloyd et al. 10.1109/TGRS.2021.3094117
5. MSWAGAN: Multispectral Remote Sensing Image Super-Resolution Based on Multiscale Window Attention Transformer C. Wang et al. 10.1109/TGRS.2024.3385752
6. Joint Sparse Representation-based Single Image Super-Resolution for Remote Sensing Applications B. Deka et al. 10.1109/JSTARS.2023.3244069
7. How Does Super-Resolution for Satellite Imagery Affect Different Types of Land Cover? Sentinel-2 Case A. Malczewska & M. Wielgosz 10.1109/JSTARS.2023.3328997
8. Semantic guided large scale factor remote sensing image super-resolution with generative diffusion prior C. Wang & W. Sun 10.1016/j.isprsjprs.2024.12.001
9. Using Super-Resolution Algorithms for Small Satellite Imagery: A Systematic Review K. Karwowska & D. Wierzbicki 10.1109/JSTARS.2022.3167646
10. Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion X. Yao et al. 10.1109/JSTARS.2024.3504865
11. Hyperspectral Image Spatial Super-Resolution via 3D Full Convolutional Neural Network S. Mei et al. 10.3390/rs9111139
12. Towards the next generation of Geospatial Artificial Intelligence G. Mai et al. 10.1016/j.jag.2025.104368
13. Remote sensing image super-resolution using multi-scale convolutional sparse coding network R. Cheng et al. 10.1371/journal.pone.0276648
14. Super Resolution by Deep Learning Improves Boulder Detection in Side Scan Sonar Backscatter Mosaics P. Feldens 10.3390/rs12142284
15. ACT-SR: Aggregation Connection Transformer for Remote Sensing Image Super-Resolution Y. Kang et al. 10.1109/JSTARS.2024.3506717
16. TR-MISR: Multiimage Super-Resolution Based on Feature Fusion With Transformers T. An et al. 10.1109/JSTARS.2022.3143532
17. A plexus‐convolutional neural network framework for fast remote sensing image super‐resolution in wavelet domain F. Deeba et al. 10.1049/ipr2.12136
18. Learning Deep Resonant Prior for Hyperspectral Image Super-Resolution Z. Gong et al. 10.1109/TGRS.2022.3185647
19. Detail-Optimized Super-Resolution Reconstruction-Based Multistage Training Strategy for Remote Sensing Semantic Segmentation B. Sui et al. 10.1109/TGRS.2023.3339842
20. RAN: Region-Aware Network for Remote Sensing Image Super-Resolution B. Liu et al. 10.1109/TGRS.2023.3330876
21. A Remote Sensing Image Super-Resolution Reconstruction Model Combining Multiple Attention Mechanisms Y. Xu et al. 10.3390/s24144492
22. Single-Image Super-Resolution for Remote Sensing Images Using a Deep Generative Adversarial Network With Local and Global Attention Mechanisms Y. Li et al. 10.1109/TGRS.2021.3093043
23. Pixel-Wise Attention Residual Network for Super-Resolution of Optical Remote Sensing Images Y. Chang et al. 10.3390/rs15123139
24. A comprehensive review on deep learning based remote sensing image super-resolution methods P. Wang et al. 10.1016/j.earscirev.2022.104110
25. Super-Resolution GAN and Global Aware Object Detection System for Vehicle Detection in Complex Traffic Environments H. Wang et al. 10.1109/ACCESS.2024.3442484
26. Dual-domain prior unfolding network for remote sensing image super-resolution J. Dong et al. 10.1007/s12145-024-01500-6
27. Remote Sensing Image Super-Resolution With Residual Split Attention Mechanism X. Chen et al. 10.1109/JSTARS.2023.3287894
28. A CNN-Transformer Embedded Unfolding Network for Hyperspectral Image Super-Resolution Y. Tang et al. 10.1109/TGRS.2024.3431924
29. A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images X. Wang et al. 10.3390/rs15205062
30. From Artifact Removal to Super-Resolution J. Wang et al. 10.1109/TGRS.2022.3196709
31. Dual Self-Attention Swin Transformer for Hyperspectral Image Super-Resolution Y. Long et al. 10.1109/TGRS.2023.3275146
32. Spectral-Spatial MLP Network for Hyperspectral Image Super-Resolution Y. Yao et al. 10.3390/rs15123066
33. SBHSR: single-band super-resolution method for hyperspectral images based on blind degradation and fusion of auxiliary band L. Bu et al. 10.1080/10106049.2023.2294901
34. The Spatiotemporal Fusion for Nighttime Light Based on SDGSAT-1 and VIIRS Data S. Zhang et al. 10.1109/TGRS.2025.3560092
35. Survey of Deep-Learning Approaches for Remote Sensing Observation Enhancement G. Tsagkatakis et al. 10.3390/s19183929
36. Double Prior Network for Multidegradation Remote Sensing Image Super-Resolution M. Shi et al. 10.1109/JSTARS.2023.3242053
37. ConvFormerSR: Fusing Transformers and Convolutional Neural Networks for Cross-Sensor Remote Sensing Imagery Super-Resolution J. Li et al. 10.1109/TGRS.2023.3340043
38. Transferred Multi-Perception Attention Networks for Remote Sensing Image Super-Resolution X. Dong et al. 10.3390/rs11232857
39. Deep Learning-Based Single Image Super-Resolution: An Investigation for Dense Scene Reconstruction with UAS Photogrammetry M. Pashaei et al. 10.3390/rs12111757
40. A Hybrid Spectral Attention-Enabled Multiscale Spatial–Spectral Learning Network for Hyperspectral Image Superresolution W. Wang et al. 10.1109/JSTARS.2024.3407953
41. A Spectral Grouping and Attention-Driven Residual Dense Network for Hyperspectral Image Super-Resolution D. Liu et al. 10.1109/TGRS.2021.3049875
42. Increasing the Geometrical and Interpretation Quality of Unmanned Aerial Vehicle Photogrammetry Products using Super-Resolution Algorithms P. Burdziakowski 10.3390/rs12050810
43. Single hyperspectral image super-resolution using a progressive upsampling deep prior network H. Wang et al. 10.3934/era.2024205
44. Paradigm shifts in super-resolution techniques for remote sensing applications G. Rohith & L. Kumar 10.1007/s00371-020-01957-8
45. Intensifying the spatial resolution of 3D thermal models from aerial imagery using deep learning-based image super-resolution A. Fallah et al. 10.1080/10106049.2022.2082544
46. Super-Resolution of Sentinel-2 Images Using a Spectral Attention Mechanism M. Zabalza & A. Bernardini 10.3390/rs14122890
47. Degradation learning for unsupervised hyperspectral image super-resolution based on generative adversarial network S. Zhang et al. 10.1007/s11760-021-01902-9
48. RGTGAN: Reference-Based Gradient-Assisted Texture-Enhancement GAN for Remote Sensing Super-Resolution Z. Tu et al. 10.1109/TGRS.2024.3359095
49. A Review of Image Super-Resolution Approaches Based on Deep Learning and Applications in Remote Sensing X. Wang et al. 10.3390/rs14215423
50. Efficient Single-image Super-resolution Using Dual path Connections with Multiple scale Learning B. Yang & G. Wu 10.1145/3570164
51. Reconstruction of 30 m Land Cover in the Qilian Mountains from 1980 to 1990 Based on Super-Resolution Generative Adversarial Networks X. Wang et al. 10.3390/rs16224252
52. Learning hyperspectral images from RGB images via a coarse-to-fine CNN S. Mei et al. 10.1007/s11432-020-3102-9
53. Minimizing the Limitations in Improving Historical Aerial Photographs with Super-Resolution Technique A. Incekara et al. 10.3390/app14041495
54. Dual-Domain Optimization Model Based on Discrete Fourier Transform and Frequency-Domain Fusion for Remote Sensing Single-Image Super-Resolution L. Shi et al. 10.1109/TGRS.2025.3540504
55. Single-Image Super-Resolution of Sentinel-2 Low Resolution Bands with Residual Dense Convolutional Neural Networks L. Salgueiro et al. 10.3390/rs13245007
56. Super-Resolution of Sentinel-2 Images Using Convolutional Neural Networks and Real Ground Truth Data M. Galar et al. 10.3390/rs12182941
57. Deep-Learning-Based Semantic Segmentation for Remote Sensing: A Bibliometric Literature Review K. Hasan et al. 10.1109/JSTARS.2023.3328315
58. Remote Sensing Image Pansharpening Using Deep Internal Learning With Residual Double-Attention Network R. Sustika et al. 10.1109/ACCESS.2024.3481466
59. Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks F. Salvetti et al. 10.3390/rs12142207
60. InstanceSR: Efficient Reconstructing Small Object With Differential Instance-Level Super-Resolution Y. Fan et al. 10.1109/TCSVT.2024.3496664
61. Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution I. Ismail et al. 10.32604/cmc.2023.043873