Parallelepiped classification uses a simple decision rule to classify multispectral data. The
decision boundaries form an n-dimensional parallelepiped classification in the image data
space. The dimensions of the parallelepiped classification are defined based upon a
standard deviation threshold from the mean of each selected class. If a pixel value lies
above the low threshold and below the high threshold for all n bands being classified, it is
assigned to that class.