Reads two portable anymaps as input.
Convolves the second using the first,
and writes a portable anymap as output.

Convolution means replacing each pixel with a weighted average of the
nearby pixels. The weights and the area to average are determined by
the convolution matrix.
The unsigned numbers in the convolution file are offset by -maxval/2 to
make signed numbers, and then normalized, so the actual values in the
convolution file are only relative.

Here is a sample convolution file;
it does a simple average of the nine immediate neighbors, resulting
in a smoothed image:

P2
3 3
18
10 10 10
10 10 10
10 10 10

To see how this works, do the above-mentioned offset: 10 - 18/2 gives 1.
The possible range of values is from 0 to 18, and after the offset
that’s -9 to 9. The normalization step makes the range -1 to 1, and
the values get scaled correspondingly so they become 1/9 - exactly what
you want.
The equivalent matrix for 5x5 smoothing would have maxval 50 and be
filled with 26.

The convolution file will usually be a graymap,
so that the same convolution gets applied to each color component.
However, if you want to use a pixmap and do a different convolution to
different colors, you can certainly do that.

At the edges of the convolved image, where the convolution matrix would
extend over the edge of the image,
pnmconvol just copies the input pixels directly to the output.