- K means algorithm is performed with different initial centroids in order to get the best clustering.

- The total cost is calculated by summing the distance of each point to its cluster centre and then summing over all the clusters.Based on the minimum overall cost achieved during each iteration of iterKMeans the pixel assignment to their respective clusters are made and final compressed image is obtained. This algorithm will run slower as the number of clusters , size of the image and number of iterations increase.-- K means algorithm is performed with different initial centroids in order to get the best clustering.

- The total cost is calculated by summing the distance of each point to its cluster centre and then summing over all the clusters.Based on the minimum overall cost achieved during each iteration of　iterKMeans　the pixel assignment to their respective clusters are made and final compressed image is obtained. This algorithm will run slower as the number of clusters , size of the image and number of iterations increase.