Clustering based color reduction -Improvements and tips-
نویسنده
چکیده
This paper presents simple yet powerful improvements in color reduction field, targeting interactive high-quality applications. Here maximum distance clustering (MDC) is used to initialize K-means clustering, which eliminates the drawback of clustering-based color reduction that tends to ignore colors with a small number of pixels. Maximum distance clustering’s speed problem due to the problem of dimensionality is solved by using a proposed sub-optimal algorithm. Furthermore, it is shown that behavior of MDC and K-means in RGB color space is different from that in CIELAB color space. Our improvements enable simple algorithms like MDC and K-means to outperform many existing color reduction algorithms. Keyword Image processing, image coding, image color analysis, image generation, clustering method
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