Color quantization using c-means clustering algorithms
作者： M. Emre Celebi , Quan Wen , Juan Chen
DOI: 10.1109/ICIP.2011.6115792
关键词: Initialization 、 Fuzzy logic 、 Artificial intelligence 、 Pattern recognition 、 Color quantization 、 Quantization (signal processing) 、 Fuzzy set 、 Linde–Buzo–Gray algorithm 、 Mathematics 、 Fuzzy clustering 、 Cluster analysis
摘要: Color quantization is an important operation with many applications in graphics and image processing. Most methods are essentially based on data clustering algorithms. Recent studies have demonstrated the effectiveness of hard c-means (k-means) algorithm this domain. Other reported similar findings pertaining to fuzzy algorithm. Interestingly, none these directly compared two types In study, we implement fast exact variants algorithms several initialization schemes then compare resulting quantizers a diverse set images. The results demonstrate that significantly slower than c-means, respect output quality former neither objectively nor subjectively superior latter.
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