Journal of Real-Time Image Processing

, Volume 10, Issue 2, pp 329–344

An effective real-time color quantization method based on divisive hierarchical clustering


    • Department of Computer ScienceLouisiana State University
  • Quan Wen
    • School of Computer Science and EngineeringUniversity of Electronic Science and Technology of China
  • Sae Hwang
    • Department of Computer ScienceUniversity of Illinois
Special Issue

DOI: 10.1007/s11554-012-0291-4

Cite this article as:
Celebi, M.E., Wen, Q. & Hwang, S. J Real-Time Image Proc (2015) 10: 329. doi:10.1007/s11554-012-0291-4


Color quantization (CQ) is an important operation with many applications in graphics and image processing. Clustering algorithms have been extensively applied to this problem. In this paper, we propose a simple yet effective CQ method based on divisive hierarchical clustering. Our method utilizes the commonly used binary splitting strategy along with several carefully selected heuristics that ensure a good balance between effectiveness and efficiency. We also propose a slightly computationally expensive variant of this method that employs local optimization using the Lloyd–Max algorithm. Experiments on a diverse set of publicly available images demonstrate that the proposed method outperforms some of the most popular quantizers in the literature.


Color quantizationClusteringDivisive hierarchical clustering

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© Springer-Verlag Berlin Heidelberg 2012