The Iterative Ant-tree for color quantization algorithm has recently been proposed to reduce the colors of an image at a low computational cost. It is a clustering-based method that generates good images compared to several well-known color quantization methods. This article proposes the modification of two features of the original algorithm: the value assigned to the parameter associated with the algorithm and the order in which the pixels of the image are processed. As a result, the new variant of the algorithm generates better images than the original and the results are less sensitive to the value selected for the parameter.

中文翻译：

---

重温迭代蚂蚁树的颜色量化算法

最近提出了用于颜色量化算法的迭代蚂蚁树以较低的计算成本减少图像的颜色。与几种众所周知的颜色量化方法相比，它是一种基于聚类的方法，可生成良好的图像。本文提出修改原算法的两个特征：分配给与算法相关的参数的值和处理图像像素的顺序。因此，该算法的新变体生成的图像比原始图像更好，并且结果对为参数选择的值不太敏感。