Workshop proceeding - final.pdf - Faculty of Information and ...

Where u ′ , v′
) is the point position in the full resolution image Im Oe , ρ u ′ , v′
) is the correlation
(
k k
(
k k
coefficient of accurate image registration, ρl
( uk
, vk
) is the correlation coefficient of rough image
registration. Through the step, we can get the registration position u ′ , ′ ) .
( * v *
k k
The final step is the estimation of rotation angle. At present the permitted rotation angle θ range is
from -10°to 10°. We divide the range into 200 angles. To each angle, we calculate its correlation
coefficient, then choose the angle θ * with the maximum correlation value.
4. Experiment results
The above algorithm was tested using many image pairs. All of the results are successful with
tolerable errors(Fig 3). In order to test the running speed, contrasting experiment was done between
the changeable resolution algorithm and standard NCC in the same running environment and
conditions, the results can be shown in table 1. The experiments show that the changeable resolution
algorithm has the same good registration results with a fast speed, only spending less than one fortieth
running time compared with the standard algorithm. Because we don’t know the true registration
positions, we compare them with the results of manual registration.
Fig 3 Raw image pairs and their registration results
Table 1 experiment results of changeable resolution algorithm based on NCC
Number of Success Running time per pair Registration error
Image pairs number (average)
(max, min, average)
Standard NCC 20 20 610s (6,0,2.6)
Changeable
resolution
algorithm
20 20 15s (6,0,2.6)
All of the tests are done in the condition of f = 2 and using Sobel operator to get the image edges.
The contrasting experiments with the NMI (normalized mutual information) and CR(correlation ratio)
algorithms have also been done( Fig 4, Table 2). From these figures and tables, we can see the
changeable resolution algorithm based on normalized cross correlation is the best choice.
30