Minimum Surface Bhattacharyya feature selection

This paper introduces a novel feature selection method called minimum surface Bhattacharyya (MSB). The method is applicable for multiple class problems utilizing supervised training. The minimum surface method selects features by means of inter-class separability. For the purposes of this paper, the method is applied to a hyperspectral data set with high correlations among the features. The method shows promise for hyperspectral analysis due to its speed and demonstrated capacity to improve classification performance.