I performed groupwise NRR after pairwise NRR where sets of images were considered. This was done using the same parameters for pairwise NRR as before. The main conclusion reached was that, based on some encouraging results, it should be reasonable to say groupwise stages after pairwise stages make a significant and positive difference. The remainder of the experiments, however, will be just pairwise for simplicity.
Multi-Scale NRR
Another larger group of experiments enabled me to study the effects
of multi-scale NRR. The results are shown in the form of chequerboard
images in Figure . In terms of resolution levels, higher
numbers mean that the images are coarser.
Judging by some later stages when resolution is increased, the conclusion reached is that the added computational effort, which is enormous, makes this increase unneeded. The increase in resolution does not reveal much new information about the image structure, at least not at the stage when registration is still far from being entirely approached.
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The results are shown for another pair of images in Figure .
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I later attempted 10 iterations at level 2, then 2 iterations at level
1, and 1 iteration at the finest level. Visual results can be seen
in Figure .
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Lastly, Figure shows 10 iterations at level 2,
6 iterations at level 1, and 6 at level 0.
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A long optimisation where I changed both the number of knot-points
and the resolution is shown in Figures and
.
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The last figure, Figure , shows an important comparison
between two large registrations. Up to 20 knot-points were
used.
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In that last figure, there is a clear difference to be seen in terms of quality, notably in favour of the image on the left. It is a chequerboard image, but it may be hard to see it because the level of overlap is high. Consequently, this registration worked a lot better and my colleagues demonstrated that the overall framework worked fully, as the remainder of this section will describe.
Roy Schestowitz 2010-04-05