The application of information entropy to the estimation of three-dimensional grain or particle size distributions from materialographic sections

Information entropy was applied to size class selection for the unfolding of grain size distributions and the results were compared with traditional forward and inverse methods using arbitrarily selected size classes. This comparison shows that information entropy provides a better representation of the data.