Optimal image colour extraction by differential evolution

Gerald Schaefer*, Lars Nolle

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review


    Differential evolution is an optimisation technique that has been successfully employed in various applications. In this paper, we apply differential evolution to the problem of extracting the optimal colours of a colour map for quantised images. The choice of entries in the colour map is crucial for the resulting image quality as it forms a look-up table that is used for all pixels in the image. We show that differential evolution can be effectively employed as a method for deriving the entries in the map. In order to optimise the image quality, our differential evolution approach is combined with a local search method that is guaranteed to find the local optimal colour map. This hybrid approach is shown to outperform various commonly used colour quantisation algorithms on a set of standard images.

    Original languageEnglish
    Pages (from-to)251-257
    Number of pages7
    JournalInternational Journal of Bio-inspired Computation
    Issue number3-4
    Publication statusPublished - 2010


    • colour map
    • colour quantisation
    • differential evolution
    • hybrid optimisation
    • K-means clustering


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