Comparison and visualization of feature space behaviour of statistical and neural classifiers of satellite imagery

Currently both statistical and neural classifiers are being used for the classification of multispectral satellite imagery. Because both classifier types are being used as `black boxes´ and because they are values based on different mathematical models the reasons for their different performance levels are not well understood. The authors have used visualization of class decision boundaries in feature space as a means to gain insight into the classification processes