In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
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8^ (pixels) (pixels) 8 :< (pixels) 
Figure 7. Similarity images (horizontal and vertical directions 
on the first and second column, respectively), regarding the 
registration of the pair of images represented in Figure 2, 
considering as similarity measure the CC (first row) and the MI 
(second row). 
Figure 8. Accuracy in the horizontal (§ x , left plots) and vertical 
(8 y , right plots) directions regarding the registration of the three 
pairs of images represented in Figure 3 (a single tile), using the 
CC as the similarity measure: Landsat/ASTER (first row); 
Orthophoto/IKONOS (second row); Orthophoto/ALOS (third 
row). 
Regarding the medium spatial resolution pair of images, the 
proposed methodology was able to achieve a subpixel accuracy 
for all considered tile sizes (Figure 8). The traditional approach 
was able to achieve a similar accuracy for templates higher than 
190x190 pixels, leading to misleading results for smaller 
templates (Figure 5). Therefore, the proposed methodology 
presents clear advantages with respect to the traditional 
approach. 
With respect to the high spatial resolution pair of images with 
urban/rural context (orthophoto/IKONOS), a subpixel accuracy 
was obtained for tiles with size 64x64 and 128x128 pixels in 
the horizontal axis, and an error less than 2 pixels in the vertical 
axis. Despite the error above the pixel in the vertical direction, 
it is quite obvious the advantage when compared to the 
traditional approach, which was quite far from the correct 
solution for all possible template sizes. For tiles with size 
256x256 pixels, the proposed methodology did not provide any 
solution, which is better than indicating a wrong solution. Even 
considering the whole images as a single tile, the obtained shifts 
were quite near the reference values. Moreover, even the 
manual identification of conjugate points was associated to a 
standard deviation of 1.8 pixels on the horizontal direction, 
supporting the difficulty of accurately registering this pair of 
images. 
For the third pair of images, composed by two high spatial 
resolution segments with rural context (orthophoto/ALOS - 
PRISM), a subpixel accuracy was also obtained for tiles with 
size 64x64 and 128x128 pixels. Once again, for tiles with size 
256x256 pixels no solution was obtained, which is better than a 
wrong solution. Considering a single tile (512x512 pixels), an 
error of around 6 pixels was obtained for both directions. This 
result indicates that a single tile should be avoided, since when 
using smaller tiles the statistical based procedure of outliers 
removal provides generally an accurate registration. 
Nevertheless, although the traditional approach tends to achieve 
an accurate solution for templates with size near the whole 
image, a closer look at the plots in Figure 5 allows for 
observing that the best obtained results are 4 pixels far from the 
correct solution. Therefore, the proposed methodology is once 
again generally better than the traditional approach. 
With respect to the computational efficiency (Figure 9), it can 
be observed that beyond the smaller tiles provide more accurate 
results, they are also associated to lower computational times, 
reinforcing their advantage. Although the presented 
computational times are considerably higher than the traditional 
approach (Figure 6), it is worth to mention that it was not under 
the scope of this work the computational time optimization. 
However, it can be largely improved, since several graphical 
outputs which are produced and stored are unnecessary to 
provide the final estimates of 8 X and 8 V . 
in the registration of the three pairs of images represented in 
Figure 3 (for different tiles dimension), using the CC as the 
similarity measure: Landsat/ASTER (+); orthophoto/IKONOS 
(*); orthophoto/ALOS (o). 
3.4 Future improvements 
The proposed approach revealed to outperform the traditional 
approach of image registration using similarity measures, in 
particular for images with clearly different radiometric content. 
Nevertheless, some preliminary tests have been performed 
which may allow for further improvements in the future. A 
visual inspection from the upper plots in Figure 10 suggest that 
a low-pass filtering may allow for extracting a profile with less 
detail, ignoring higher variability related to the spectral 
characteristics. Therefore, a 2 nd -order low-pass Butterworth 
filter, with a normalized cutoff frequency at 0.1 was applied to