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Parameters to setup for the cross-correlation algorithm are in all cases:
- The size of the search area in x and y. Given a starting point,
how far will be searched in pixels around the point to find for a
matching point? Setting this value depends on the expected level of
accuracy for the provided positions.
- The size of the measurement area in x and y. Given a candidate
position for a match, how many pixels should be used to compute the
cross-correlation criterion? Figure 5 shows the
importance of choosing a right measurement area size.
Figure 5:
Importance of a right definition for the measurement area. The
measurement areas are shown as overlapping dark boxes over the image.
Above: it is too small, as it would induce a periodical pattern effect
(any other star is a good candidate). Below: it looks large enough to
prevent false detections.
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As specified, parameter settings depend on the quality of the input
estimates for the offsets. The implementation gives the following
possibilities for input estimates: header offsets, file offsets, or no
offsets (automatic search). Each case is described hereafter.
One word about edge effects: computing a cross-correlation criterion for
a point lying on an image edge would mean a loss in precision and
probably artefacts. For this reason, it has been decided not to compute
any cross-correlation if the involved point lies too close to an edge in
one of the two input images. This sets a constraint on the choice of
correlating point only.
Next: Header offsets
Up: Cross-correlation
Previous: Example
Nicolas Devillard
1999-06-21