HYPERSPECTRAL CLUSTERING HAS EXPERIENCED DECADES OF DEVELOPMENT, AND A GREAT QUANTITY OF METHODS HAS BEEN PUT FORWARD. are based on the assumption that a cluster has a " ball-like " structure in the feature space. Starting with random initializations, such methods iteratively update the centroids and their associated pixel partitions until the overall partition error meets the tolerance requirement