Contextual color quantization algorithm

M. P. Yu, K. C. Lo
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引用次数: 1

Abstract

We propose an heuristic approach to color-quantize images with contextual information taken into consideration. The idea is to locate the regions of an image having the greatest need for colors, and allocate more quantization levels to them. We achieve this by scanning the elements of the input image in a way determined by their local intensity and select the color representatives that comprise the color map according to their local popularity. The overall performance of the color quantization algorithm is evaluated on representative set of artificial and real-world images. The results show a significant image quality improvement compared to some of the other color quantization schemes.
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上下文颜色量化算法
我们提出了一种启发式方法,考虑到上下文信息的颜色量化图像。这个想法是定位图像中最需要颜色的区域,并为它们分配更多的量化级别。我们通过扫描输入图像的元素,以一种由它们的局部强度决定的方式来实现这一点,并根据它们的局部流行度选择组成颜色图的颜色代表。在具有代表性的人工图像集和真实图像集上对颜色量化算法的总体性能进行了评价。结果表明,与其他一些颜色量化方案相比,图像质量得到了显著改善。
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