Super-resolution Processing

Super-Resolution Processing is a signal processing technique in radar systems that belongs to the class of resolution enhancement methods and is distinguished by its ability to resolve closely spaced targets beyond the classical diffraction limit through advanced spectral estimation, sparse modeling, or machine learning-based inversion.

1.5K

Publications

89.6K

Citations

4.8K

Authors

1.1K

Institutions

Publications per year

2017–2026

807

Authors

4.8K

  1. RT
    Radu Timofte

    ETH Zurich, Switzerland

    28 publications · 3.9K citations

    22

    h-index

  2. JY
    Jianyu Yang

    University of Electronic Science and Technology of China, China

    20 publications · 716 citations

    16

    h-index

  3. JJ
    Junjun Jiang

    Harbin Institute of Technology, China

    22 publications · 1.4K citations

    16

    h-index

  4. YH
    Yulin Huang

    University of Electronic Science and Technology of China, China

    18 publications · 659 citations

    15

    h-index

  5. YZ
    Yin Zhang

    University of Electronic Science and Technology of China, China

    17 publications · 644 citations

    15

    h-index

1–5 of 4.8K

Venues

  1. IEEE Transactions on Image Processing

    44 publications · 4.8K citations

    35

    h-index

  2. 30

    h-index

  3. arXiv (Cornell University)

    Repository · 46 publications · 2.1K citations

    21

    h-index

  4. 19

    h-index

  5. Remote Sensing

    19 publications · 1.7K citations

    16

    h-index

1–5