Histogram-based Transfer Functions

Histogram-Based Transfer Functions is a transfer function design method that employs the data histogram as the genus to inform opacity and color mappings, differentiating itself by leveraging the distribution of scalar values to automatically identify and emphasize prominent features through opacity assignment based on frequency.

10

Publications

892

Citations

29

Authors

16

Institutions

Publications per year

2017–2026

5

Authors

29

  1. AA
    Assaf Arbelle

    IBM (United States), United States

    2 publications · 46 citations

    2

    h-index

  2. XG
    Xinyang Geng

    University of California, Berkeley, United States

    2 publications · 592 citations

    2

    h-index

  3. MA
    Mor Avi-Aharon

    Ben-Gurion University of the Negev, Israel

    2 publications · 46 citations

    2

    h-index

  4. AS
    Angela S. Lin

    University of California System, United States

    2 publications · 592 citations

    2

    h-index

  5. AA
    Alexei A. Efros

    University of California, Berkeley, United States

    2 publications · 592 citations

    2

    h-index

1–5 of 29

Venues

  1. arXiv (Cornell University)

    Repository · 2 publications · 45 citations

    2

    h-index

  2. Journal of Imaging

    1 publications · 12 citations

    1

    h-index

  3. IEEE Transactions on Image Processing

    1 publications · 66 citations

    1

    h-index

  4. Eurographics

    Repository · 1 publications · 43 citations

    1

    h-index

  5. Information Sciences

    1 publications · 68 citations

    1

    h-index

1–5