Two-stage color palettization for error diffusion

Niloy J. Mitra, Maya R. Gupta*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Image-adaptive color palettization chooses a decreased number of colors to represent an image. Palettization is one way to decrease storage and memory requirements for low-end displays. Palettization is generally approached as a clustering problem, where one attempts to find the k palette colors that minimize the average distortion for all the colors in an image. This would be the optimal approach if the image was to be displayed with each pixel quantized to the closest palette color. However, to improve the image quality the palettization may be followed by error diffusion. In this work, we propose a two-stage palettization where the first stage finds some m < < k clusters, and the second stage chooses palette points that cover the spread of each of the M clusters. After error diffusion, this method leads to better image quality at less computational cost and with faster display speed than full k-means palettization.

Original languageEnglish (US)
Pages (from-to)207-217
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2002
Externally publishedYes
EventHuman Vision and Electronic Imaging VII - San Jose, CA, United States
Duration: Jan 21 2002Jan 24 2002


  • Color clustering
  • Color palettization
  • Multi-level halftoning

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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