Referring and quoting the SNIC (Simple Non-Iterative Clustering) paper:
In each k-means iteration, SLIC evolves a centroid by computing the average of all pixels that are closest to it in terms of d and, therefore, have the same label as the centroid..
Thus, unlike SLIC, which requires multiple k-means iterations to update the centroids, we update the centroids in a single iteration..
So, SLIC is based on K-Means and SNIC is an improved version of SLIC. In K-Means if the similar pixels are distant from each other they are still clustered into one class let's say class0. But while implementing SNIC, I have observed that it groups a bunch of pixels together (screenshot is attached here below) and assigns different colors to each of the bunch/group of pixels.
Do these different colors indicate different classes or can two groups of pixels indicate a similar class?