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An adjustable algorithm for color quantization
Authors:Zhou Bing  Shen Junyi  Peng Qinke
Affiliation:

aDepartment of Computer Science, Northeastern University at QinHuangDao, 066004 QinHuangDao, China

bInstitute of Computer Software, Xi’an Jiaotong University, 710049 Xi’an, China

cInstitute of System Engineering, Xi’an Jiaotong University, 710049 Xi’an, China

Abstract:Color quantization is an important technique in digital image processing. Generally it involves two steps. The first step is to choose a proper color palette. The second step is to reconstruct an image by replacing original colors with the most similar palette colors. However a problem exists while choosing palette colors. That is how to choose the colors with different illumination intensities (we call them color layers) as well as the colors that present the essential details of the image. This is an important and difficult problem. In this paper, we propose a novel algorithm for color quantization, which considers both color layers and essential details by assigning weights for pixel numbers and color distances. Also this algorithm can tune the quantization results by choosing proper weights. The experiments show that our algorithm is effective for adjusting quantization results and it also has very good quality of quantization.
Keywords:Color quantization  Cluster feature  Octree  Digital image processing  Weighted product
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