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A controlled map stays true.
Decades of orbital imagery have been stitched into mosaics tied to laser-altimeter ground control. At the south pole that map is accurate to metres — it is the fixed reference everything else is measured against.
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A new image arrives in the wrong place.
A fresh high-resolution image is placed on the Moon using predicted orbit and pointing. Small errors in those predictions move it away from the ground it actually shows — close enough to look right, too far to be trusted.
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Sun angle changes everything.
Near the pole the Sun never climbs far above the horizon. The same crater throws a different shadow on every pass, so two images of the same ground can share almost no pixels that look alike.
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Matching finds the same ground.
Contrast is normalised, then learned features propose tie-points: places where the new image and the map show the same ground. When shading defeats keypoints, foundation-model embeddings and area correlation take over.
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Verification rejects what disagrees.
Not every tie-point is right. RANSAC keeps only those that agree on one geometric transform, then checks they spread across the whole frame instead of clustering in one corner.
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Registered.
The verified transform moves the image onto the map's grid. It is exported as a GeoTIFF that opens on the right ground in any GIS, alongside a report of how accurate the fit is.
