Date: 06 Nov 2012

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

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Abstract

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.