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.
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This publication was made possible by grants from the Louisiana Board of Regents (LEQSF2008-11-RD-A-12), US National Science Foundation (0959583, 1117457), and National Natural Science Foundation of China (61050110449, 61073120).
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Celebi, M.E., Wen, Q. & Hwang, S. An effective real-time color quantization method based on divisive hierarchical clustering. J Real-Time Image Proc 10, 329–344 (2015). https://doi.org/10.1007/s11554-012-0291-4
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DOI: https://doi.org/10.1007/s11554-012-0291-4