The Fuzzy Convolution operation creates a single classification layer
by calculating the total weighted inverse distance of all the classes
in a window of pixels. Then, it assigns the center pixel in the class
with the largest total inverse distance summed over the entire set of
fuzzy classification layers.
This has the effect of creating a context-based classification to
reduce the speckle or salt and pepper in the classification. Classes
with a very small distance value remain unchanged while classes
with higher distance values may change to a neighboring value if
there is a sufficient number of neighboring pixels with class values
and small corresponding distance values. The following equation is
used in the calculation: