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2.7.2 Defining Initial Matches
The first step is to determine possible matches
between an interest point in the first image and
any number of interest points in the second
image. A geometric transformation exists
between the two images, supplied by a higher
level in the pyramid or by the operator. This is
used to predict the position of a point from the
first image, in the second image. From this
predicted position a search is made within a
window of specified size for interest points.
Any points found inside this window are
considered as possible matches.
The result of this procedure is a list with the
identity of a point from the first image
associated to the identity of possible matches in
the second image. It should be noted that a
single point in the first image can be matched to
several points in the second image, and vica
versa.
2.7.3 Cross Correlation
The above procedure tends to produce a large
number of matches, some of which are
ambiguous. Considering a given conjugate point
pair, an image chip is placed around each pixel
and image cross correlation is calculated. This
may require the resampling of one of the chips
if the is significant rotational or scale
differences between the two images. If the
cross correlation value falls below a given
threshold then this conjugate pair is removed
from further consideration.
131
2.7.4 Robust Transformation
Estimation
The resultant conjugate points from the above
procedure are then processed by a Robust
Transformation Estimation procedure. This
procedure seeks to determine a geometric
transformation between the two images based
on the conjugate points. It is an iterative
solution in which each conjugate pair is initially
weighted. These weightings are updated based
on the calculated point residuals for each
iteration. Outliers are removed at each
iteration, and the procedure continues till
convergence is achieved, or a maximum number
of iterations has occurred. The initial weights
of the conjugate points are based on each points
‘weight’ calculated by the interest operator.
The robust transformation estimation results in
a trimmed set of conjugate points, in which
unlikely conjugate points having been rejected.
A new geometric transformation is also
defined.
It is likely that some ambiguities still exist,
with a single point in the first image matched to
more than one point in the second image, or
visa versa. These ambiguities are removed by
selecting the conjugate point pair with the
lowest residual (weight). Once ambiguities
have been removed a new geometric
transformation is defined.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996