Palette Generation

Palette Generation is a computational method in image quantization that determines an optimal subset of representative colors from a source image or color space, distinguishing itself by strategically selecting and organizing these colors to minimize visual distortion while reducing the color depth of the output.

125

Publications

6.4K

Citations

401

Authors

185

Institutions

Publications per year

2017–2026

44

Authors

401

  1. YH
    Yu‐Chen Hu

    Providence University, Taiwan

    3 publications · 78 citations

    3

    h-index

  2. GS
    Gerald Schaefer

    Loughborough University, United Kingdom

    3 publications · 40 citations

    3

    h-index

  3. TD
    Thomas D. LaToza

    Carnegie Mellon University, United States

    3 publications · 170 citations

    3

    h-index

  4. YY
    YoungSeok Yoon

    Carnegie Mellon University, United States

    3 publications · 170 citations

    3

    h-index

  5. BA
    Brad A. Myers

    Carnegie Mellon University, United States

    3 publications · 170 citations

    3

    h-index

1–5 of 401

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 7 publications · 549 citations

    7

    h-index

  2. Computer Graphics Forum

    5 publications · 346 citations

    5

    h-index

  3. ACM Transactions on Graphics

    TOG · 5 publications · 451 citations

    5

    h-index

  4. IEEE Transactions on Image Processing

    5 publications · 184 citations

    5

    h-index

  5. The Imaging Science Journal

    3 publications · 78 citations

    3

    h-index

1–5