These classification methods are also known as parametric
(i.e. based on distribution parameters) and the classification is performed
on the basis of parametric signatures defined by statistical
parameters (e.g., mean and covariance matrix) and attributes, such as,
the number of spectral bands, mean, minimum and maximum value
in each band, as well as the number of pixels and covariance matrix
for each training cluster.