K-means is only grouping all of the pixels in to K disjoint clusters, not actually altering the value of the pixels. Taking an entire cluster of pixels and shifting their values in the RGB space could produce some very interesting images. For example, you could easily make all of the almost-white pixels slightly blue. There would be no loss of variety among the pixels, they would just all have their blue values bumped up.

You compute 'centroids' which denote the centers of the clusters, but you don't have to change the values of all points to the centers of the clusters.

In other words, you can maintain the detail in RGB space (as this author has) while reorganizing things in location space by their k-means clusters.