SLIC主要运用K-means聚类算法进行超像素的处理，聚类算法中的距离度量不仅仅包括颜色空间的颜色距离还包括像素坐标的欧氏距离。所以K-means聚类的中心点由五维向量组成。其中包括，记录LAB颜色空间下的像素以及该像素点的XY坐标，由于XY坐标不能和颜色空间直接进行计算，所以添加了一个紧密度的参数。(slic superpixelSLIC mainly uses the K-means clustering algorithm for ultra pixel processing, the distance measurement in the clustering algorithm includes not only the color distance of the color space, but also the Euclidean distance of the pixel coordinates. Therefore, the central point of K-means clustering consists of five dimensional vectors. These include the recording of pixels in the LAB color space, and the XY coordinates of the pixel points, so that a parameter of compactness is added because the XY coordinates cannot be directly computed with the color space.)