Transfer Function Optimization

Transfer Function Optimization is a computational methodology within scientific volume visualization that systematically refines the mapping of data values to optical properties—such as color and opacity—to enhance the visual representation of volumetric features through targeted improvements in perception, specificity, or task-driven criteria.

26

Publications

1.2K

Citations

74

Authors

30

Institutions

Publications per year

2017–2026

6

Authors

74

  1. IB
    Imma Boada

    Universitat de Girona, Spain

    2 publications · 76 citations

    2

    h-index

  2. MS
    Mateu Sbert

    Universitat de Girona, Spain

    2 publications · 76 citations

    2

    h-index

  3. CC
    Chee‐Kong Chui

    National University of Singapore, Singapore

    2 publications · 55 citations

    2

    h-index

  4. MR
    Marc Ruiz

    Universitat de Girona, Spain

    2 publications · 76 citations

    2

    h-index

  5. MF
    Miquel Feixas

    Universitat de Girona, Spain

    2 publications · 76 citations

    2

    h-index

1–5 of 74

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 2 publications · 109 citations

    2

    h-index

  2. 2

    h-index

  3. 1

    h-index

  4. IFAC-PapersOnLine

    1 publications · 12 citations

    1

    h-index

  5. The Visual Computer

    1 publications · 39 citations

    1

    h-index

1–5