1. A method for processing hyperspectral image data, comprising: receiving reduced dimensionality data associated with hyperspectral image data, the data including a set of pixels each represented by a spectral vector, a set of basis vectors associated with generating the reduced dimensionality data from the hyperspectral image data, and anomaly data associated with the hyperspectral image data; using a processor, establishing an initial set of clusters for the reduced dimensionality data, the initial set of clusters having cluster centers being based on the set of basis vectors; using the processor, iteratively assigning pixels from the reduced dimensionality data to one of the set of clusters and modifying the cluster centers based on the assigned pixels, for a given cluster, the pixels assigned to the given cluster being similar in that they have similar distances to the cluster center of the given cluster; outputting clustered pixel assignments and modified cluster centers associated with the hyperspectral image data; and wherein iteratively assigning pixels includes excluding anomalous pixels, which correspond to the anomaly data, from being assigned to the set of clusters.