A New Color Image Quantization Algorithm Based on Fuzzy Kernel Clustering
Автор: MA Yu-jie
Журнал: International Journal of Education and Management Engineering(IJEME) @ijeme
Статья в выпуске: 2 Vol.1, 2011 года.
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A new color image quantization algorithm based on fuzzy kernel clustering is studied in this paper. Firstly, the original image is quantized to 256 colors using the octree algorithm. Secondly, based on the quantitative relation of the NBS distance and the color difference of human vision, the initial clustering centers and number are determined automatically. Thirdly, the clustering center color values are modified by use of the fuzzy kernel clustering algorithm in the Munsell space. And then, a color image quantization effect is achieved. At last, simulations are performed on the presented algorithm, and the simulation result shows that the presented algorithm not only can solve the problem of giving the number of quantization in advance but also has better quantization effect than the octree algorithm and fuzzy c-means algorithm in the same quantization number.
Image, Quantization, Fuzzy Kernel Clustering, Octree, Fuzzy C-means
Короткий адрес: https://sciup.org/15013575
IDR: 15013575
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