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A New Human Perceptional Color Quantization Algorithm

机译:一种新的人类感知色量化算法

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摘要

The goal of color quantization is to remarkably reducing the number of colors in an image without obviously degrading its visual effect. The study of this paper proposed a new human perceptional color quantization algorithm which minimizing the quantization distortion under the perceptually uniform Munsell NBS distance measurements. This method chooses the most frequently used colors as seeds with a limitation of the optimal minimal distance between seeds, which is computed using an iterative algorithm. Experiments show that the proposed method outperforms the Minimal Variance Quantization (MVQ) algorithm on quantization distortion and perceptual effect.
机译:颜色量化的目标是显着减少图像中的颜色数量,而不会显着降低其视觉效果。本文的研究提出了一种新的人类感知颜色量化算法,最小化了感知均匀的Munsell NBS距离测量下的量化失真。该方法选择最常用的颜色作为种子,其使用迭代算法计算的种子之间的最佳距离。实验表明,所提出的方法优于数量差异(MVQ)算法的量化失真和感知效果。

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