Comparing two images with Imaging Lingo

Hi everybody!
Here's the deal: I have two grayscale images and I want to
find out where they match the closest. I want to compute the
difference between the two and find the spot with the least
difference.
So I copy one into the other with the #ink: 38 ("subtract")
and wherever is the darkest spot the images are closest alike.
Right? Wrong!
When Director subtracts one color from the other and the
result is below 0, Director adds another 256 so the result is
always between 0 and 255. When I use "subtract pin" the result is
almost completely black, so this doesn't help as well. I thought
about simulation high dynamic range images with some stupid hacks
but to no avail.
Where am I thinking wrong? Can I compute the difference with
Imaging Lingo? Any help is greatly appreciated.

Here's an idea: use reverse ink to copy one image onto the
other. The areas which are most nearly white in the resulting image
will be the closest match. You can adapt the code found at
nonlinear.openspark.com
to isolate the pixels that are nearly white.

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[Attachment Test.llb, see below]
Attachments:
Test.llb ‏184 KB

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ef2019c7-080c-4475-9cf4-2cf1b1057a41 wrote:
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Comparing two images with Imaging Lingo

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