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until the maximum mutual information is founded and the 
corresponding location is the homologous point. 
4. ORTHO-RECTIFYING BY TIN SMALL REGION 
Lots of homologous feature point couples distributed in the 
simulated SAR image and the real SAR image provide a good 
control for fine image registration because these points are tie 
points between the real SAR and simulated SAR and they can 
be used to build the precise pixel-to-pixel relationship. It is an 
ideal solution to construct many small image regions using 
these homologous feature points and then rectify those small 
regions one by one. It is an easy and very effective method to 
construct many triangle regions using triangle irregular network 
(TIN). The vertices of the triangles are feature points and TIN 
can cover the whole image. The mapping relationship between 
the vertices of two triangles is known, so the relationship of the 
pixels within the triangle can be calculated by affine translation. 
Therefore the simulated image can be registered with real SAR 
image finely. Figure 3 shows the mapping relationship between 
one triangle in real SAR image and that in simulated SAR 
image as well as the mapping relationship between the 
simulated SAR image and DEM. 
Homologous feature points 
Figure 3. Map relationship between small regions and DEM 
The real SAR image can be rectified based on the mapping 
relationship between simulated SAR and DEM if the simulated 
SAR image is finely registered with the real SAR image. 
Therefore a pixel in real SAR image is output into the 
corresponding position of DEM by the help of the 
corresponding simulated SAR pixel. Figure 4 demonstrates the 
realization method to rectify the SAR image based on DEM in 
detail. 
Figure 4. Principle of ortho-rectifying SAR by DEM 
Feature points detected in the simulated SAR image and TIN 
constructed by these feature points are shown in figure 5, while 
the homologous feature points extracted in the real SAR image 
by mutual information matching and the constructed TIN are 
also shown in figure 6. The top-right part in figure 5 and figure 
6 is a magnified part respectively. We can see that the extracted 
feature points and constructed TIN are correct. Figure 7 shows 
a Radarsat-1 SAR image with a geometrical resolution of 
12.5m by 12.5m and its most parts are mountains, and figure 8 
is the actual relief map of the same area. The geometrical 
distortion of the SAR image is very serious by comparing the 
SAR image with the relief map, because SAR image is side 
look. Figure 9 is the orthorectified image using DEM by the 
method proposed in the paper, the distortion owing to terrain 
undulation is eliminated and the rectified SAR image is very 
similar to the relief map shown in figure 8. Figure 10 and figure 
11 show the local magnified result of orthorectified SAR and 
relief map in the same area. 
We merge the orthorectified SAR image into the relief map in 
order to evaluate the accuracy. Figure 12 gives the merged 
result and it is very satisfactory. We also check the accuracy by 
measuring the coordinates of 16 outstanding points in DEM and 
the orthorectified SAR image. The actual coordinates, 
orthorectified coordinates and their difference are listed in table 
1. The rectified horizontal accuracy reaches 27.46m which is 
about 2 times bigger than the resolution of the SAR image.