Using hierarchical histogram representation for the EM clustering algorithm enhancement

Abstract

This paper is devoted to EM clustering improvement using hierarchical multivariate histogram for probability density representation. We propose to store and operate with the image histogram by means of a special tree data structure. This allows to speed up computations in the case of multivariate input. We also answer the questions of the algorithm initialization and offer an initialization rule, which exploits the proposed histogram-tree structure. We have tested our algorithm modification and initialization rule using remote sensing images. Obtained results have confirmed that the modified algorithm is faster and the initialization rule provides better clustering in comparison with the traditional EM algorithm implementation.