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Title
Mapping without the sun
Author
Zhang, Jixian

163
if | Ax, |> Tx or | Ay, \> T y , (Ax, A y )-(Bx, By) is
mismatching points.
6. EXPERIMENT RESULT
The data for experiment are divided into 4 groups.
In the first group, A1 is TM image in band 3 whose resolution
is 30m and size is 726 X 623. B1 is SPOT image whose
resolution is 10m and size is 1360 X 1138. Image A1 is obtained
in August 2000 and B1 is obtained in May 2000.
In the second group, A2 is TM image in band 8 whose
resolution is 15m and size is 185 X 1105. B2 is SPOT image
whose resolution is 10m and size is 1360 X 1138. Image A2 is
obtained in June 2003 and B2 is obtained in May 2000.
In the third group, A3 is aerial image whose resolution is 10m
and size is 1024 X 1024. B3 is SPOT image whose resolution is
5m and size is 2048 X 2800. Image A3 is obtained in October
1993 and B3 is obtained in September 2004.
In the fourth group, A4 is IKONOS image whose resolution is
lm and size is 8831 X 9090. B4 is SPOT image whose
resolution is 10m and size is 1360 X 1138. Image A4 is obtained
in October 2003 and B4 is obtained in May 2000.
The four group images and registration results are shown as
below.
There are much difference between A1 and B1 on acquisition
time, ground resolution, sensor and gray feature, moreover, the
rotation angle is 5 degree.
Fig. 1(A1), (Bl) show the result of registration for TM Image
and SPOT image (Threshold J' q for Forstner is 0.6), the feature
points distributes evenly because of the evenly control. Under
the initial steering by 6 pairs of artificial selection exact
homologous, we get 137 pairs of homologous using invariant
moments similarity measurement combined with global
relaxation matching. Finally, the points whose number are 59,
97, 134 and 135 is eliminated because they are mismatching
points by using of the method of quadratic polynomial model
detection.
We used other 2 kinds of method to process the four groups
data and the result is given by table 1. Method 1 is proposed in
document [4], Method 2 is proposed in document [6], Method 3
is proposed in this paper.
From the experiment results, and compared with other method,
we found this method has the suitable matching precision, the
matching error maintains about 0.5 pixels. The matching
method proposed in the paper, adapting the multi-sensor remote
sensing image with high accuracy, in homogenizing control of
feature points, mismatches elimination as well as the global
relaxation algorithm, has the optimal result in the matching
speed and the precision.
(Al)
(B2)
(Bl)
(B3) (B4)
Figure 1. The result of registering between multi-source remote sensing images