Topological Compression

Topological Compression is a data reduction technique that preserves essential topological features of a scalar field or dataset by encoding its critical structures—such as connected components, saddles, and peaks—using a simplified topological representation, thereby enabling efficient storage and visualization while maintaining fidelity to the underlying topology.

39

Publications

2.9K

Citations

93

Authors

47

Institutions

Publications per year

2017–2026

3

Authors

93

  1. HT
    Holger Theisel

    Otto-von-Guericke-Universität Magdeburg, Germany

    4 publications · 126 citations

    4

    h-index

  2. JR
    Jarek Rossignac

    Georgia Institute of Technology, United States

    3 publications · 1.3K citations

    3

    h-index

  3. KO
    Kyosuke Ogawa

    Toshiba (Japan), Japan

    2 publications · 127 citations

    2

    h-index

  4. JS
    Jack Snoeyink

    University of North Carolina at Chapel Hill, United States

    2 publications · 58 citations

    2

    h-index

  5. YT
    Yasunori Tanaka

    Kanazawa University, Japan

    2 publications · 127 citations

    2

    h-index

1–5 of 93

Venues

  1. Computer Graphics Forum

    3 publications · 106 citations

    3

    h-index

  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 738 citations

    2

    h-index

  3. IEEE Visualization

    Conference · 1 publications · 44 citations

    1

    h-index

  4. Science

    1 publications · 39 citations

    1

    h-index

  5. OpenGrey (Institut de l'Information Scientifique et Technique)

    Repository · 1 publications · 118 citations

    1

    h-index

1–5