Super-resolution

Super-Resolution is a raster data processing technique that enhances the spatial resolution of geospatial imagery by inferring and reconstructing fine-grained details from coarse-grained input through learned or algorithmic models.

6.9K

Publications

563.9K

Citations

21.7K

Authors

3.5K

Institutions

Publications per year

2017–2026

4.5K

Authors

21.7K

  1. RT
    Radu Timofte

    ETH Zurich, Switzerland

    71 publications · 16.2K citations

    37

    h-index

  2. CD
    Chao Dong

    Shenzhen Institutes of Advanced Technology, China

    46 publications · 21.5K citations

    34

    h-index

  3. TS
    Thomas S. Huang

    University of Illinois Urbana-Champaign, United States

    39 publications · 14.2K citations

    31

    h-index

  4. JJ
    Junjun Jiang

    Harbin Institute of Technology, China

    45 publications · 3K citations

    29

    h-index

  5. YZ
    Yulun Zhang

    Northeastern University, United States

    36 publications · 9.1K citations

    28

    h-index

1–5 of 21.7K

Venues

  1. IEEE Transactions on Image Processing

    212 publications · 39.6K citations

    88

    h-index

  2. Nature Communications

    131 publications · 14.5K citations

    67

    h-index

  3. IEEE Transactions on Geoscience and Remote Sensing

    169 publications · 13.6K citations

    66

    h-index

  4. arXiv (Cornell University)

    Repository · 263 publications · 21.2K citations

    58

    h-index

  5. Scientific Reports

    142 publications · 7.6K citations

    52

    h-index

1–5