77ze International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008
A test field suitable for such procedures is seen in Figure 1. A
closer look at the extracted point and line features is given in
Figures 2a and 2b, respectively. In Figure 2b it is clearly seen
that the line features are composed of individual points.
Figure 1: Suggested calibration test field with
automatically extracted point and linear features
Figure 2a: Point feature
Figure 2b: Line feature
3. CAMERA STABILITY
It is well known that professional analogue cameras, which
have been designed specifically for photogrammetric purposes,
posses strong structural relationships between the focal plane
and the elements of the lens system. Amateur digital cameras,
however, are not manufactured specifically for the purpose of
photogrammetric mapping, and thus have not been built to be as
stable as traditional mapping cameras. Their stability thus
requires thorough analysis. If a camera is stable, then the
derived IOP should not vary over time. In the work done by
Habib and Pullivelli (2006b), three different approaches to
assessing camera stability are outlined, where two sets of IOP
of the same camera that have been derived from different
calibration sessions are compared, and their equivalence
assessed. In their research, different constraints were imposed
on the position and orientation of reconstructed bundles of light
rays, depending on the georeferencing technique being used.
The hypothesis is that the object space that is reconstructed by
two sets of IOP is equivalent if the two sets of IOP are similar.
The three different approaches to stability analysis are briefly
outlined in the following sections. In these methods, two sets of
IOP are used to construct two bundles of light rays. A synthetic
regular grid is then defined in the image plane. The distortions
are then removed at the defined grid vertices, using the two sets
of IOP in order to create distortion-free grid points. The
distortion-free grid points of each IOP are then compared to
assess their similarity.
3.1 Zero Rotation Method (ZROT)
In the ZROT method, a constraint is applied on the bundles
such that they must share the same perspective centre and have
parallel image coordinate systems. If the two IOP sets are
equivalent, then the coordinates of the distortion-free vertices in
the two synthetic grids should be the same. Therefore, the
differences in the x and y coordinates between the two
distortion-free grids are used to estimate the offset between the
two sets of IOP. When the principal distances of the two sets of
IOP are different, the distortion-free grid points from one IOP
are projected onto the image plane of the other, before the x and
y coordinate offsets are measured (Figure 3). The similarity
between the two bundles is then determined by computing the
Root Mean Square Error (RMSE) of the offsets. If the RMSE is
within the range defined by the expected standard deviation of
the image coordinate measurements, then the camera is
considered stable. This similarity imposes restrictions on the
bundle position and orientation in space, and thus has similar
constraints to those imposed by direct georeferencing with
GPS/INS. Therefore, if the IOP sets are similar according to the
ZROT method, the relative quality of the object space that is
reconstructed based on the direct georeferencing technique
using either IOP set will also be similar.
Ray from Bundle I
Ray from Bundle II
Original Image Grid Points
Distortion-free Grid Point using IOPi
Distortion-free Grid Point using IOP n
Projected Grid Point of IOP tI
Figure 3: The offset between distortion-free coordinates of conjugate
points in the ZROT method
3.2 Rotation Method (ROT)
In comparison with the ZROT method, which restricted the
bundles orientation, this method allows the comparison of
bundles that share the same perspective centre but which have
different orientation in space (Figure 4). The purpose of the
stability analysis is to determine if conjugate light rays coincide
with each other, and this should be independent of the bundle
orientation. This method checks if there is a set of rotation
angles (cd, (p, k) that can be applied to one bundle to produce the
other. A least-squares adjustment is performed to determine the
rotation angles, and the variance component of the adjustment,
which represents the spatial offset between the rotated bundles
in the image plane, is used to determine the similarity of the
two bundles. The bundles are deemed similar if the variance
component from the least squares adjustment is in the range of
the variance of the image coordinate measurements. This
similarity imposes restrictions on the bundle positions in space,
and thus has similar constraints to those imposed by GPS
controlled photogrammetric georeferencing. Therefore, if the
IOP sets are similar according to the ROT method, the relative
quality of the object space that is reconstructed based on the
GPS controlled georeferencing technique, using either IOP set,
will also be similar.
P.C. (0, 0,0)
Pi fri, yi,-Ci)
R (co.iil), k)
Pafrn,Vn,-cn)
Figure 4: The two bundles in the ROT method are rotated to reduce the
angular offset between conjugate light rays
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