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Mapping without the sun
Zhang, Jixian

tical data. IEEE
ation of Different
, 2003.
metric for image
rence on Image
on measure for
ïtters, 38(7):313-
al image quality
-84, 2002.
Hongjian You 3 Fu Kun a
a Institute of Electronics, Chinese Academy of Sciences, Beijing 100080-youhongjian@263.net
KEY WORDS: DEM, simulated SAR, orthorectification, TIN
A method to orthorectify spacebome SAR based on DEM is described in this paper. DEM data is used to generate a simulated SAR
image according to range-Doppler principle and experiential backscatter coefficient, and then we apply Harris operator and mutual
information matching to extract homologous points distributed in real SAR image and simulated SAR image. Real SAR image can
be registered finely with simulated SAR image based on triangle irregular network (TIN) that is constructed using the extracted
homologous points. The real SAR image is then orthorectified based on the relationship between real SAR and simulated SAR, as
well as the relationship between simulated SAR and DEM. The method is used to process Radarsat-1 SAR image and the processed
result is satisfactory.
Being an effective earth observation technique, Synthetic
aperture radar (SAR) is being paid importance to and it is
complimentary to optical remote sensing owing to its all-
weather capability. Several satellite SAR systems have been
launched since the first space-bome SAR run in 1978 and
Chinese first space-bome SAR used for environment
monitoring will also be launched soon. The space-bome SAR
image must be ortho-rectified in order to provide an image
without any distortion before it is widely used. Generally
digital elevation model (DEM) is used to eliminate the
influence of terrain, especially in mountain areas. There are two
methods to rectify SAR using DEM (Johnsen,1995), one is to
fine the satellite orbit more accurately using ground control
points (GCP) that is collected in topography map and then the
DEM is combined with fine orbit parameters to rectify the SAR
image. The other one is to generate a simulated SAR image
using DEM directly, and then the real SAR image is rectified
into the geo-referenced coordinates of DEM after the
corresponding relationship between the simulate SAR image
and real SAR image is determined by matching manually or
automatically. The latter method is an effective method because
GCP is not needed and only DEM is needed, therefore it is
possible to ortho-rectify SAR image automatically. The local
distortion cannot be considered using the former method, and
the simulated SAR image must be registered finely with real
SAR image in order to eliminate the local distortion if the latter
method is used. A new method to register the simulated SAR
with real SAR from registration register to fine registration is
proposed in this paper, and then space-bome SAR is ortho-
rectified based on finely registered small region. 2
Simulated SAR image can be generated based on SAR imaging
geometry principle using the satellite orbit parameters and
DEM. Both the image coordinates and gray-value
corresponding to the grid location of DEM must be calculated
in order to generate a simulated SAR image. We can use the
range-Doppler formula to solve the image coordinates of DEM
grid point because the SAR image is slant image which is
synthetic using Doppler principle. The gray-level of SAR must
be also simulated in addition to image location. The backscatter
coefficient influences the gray-level of SAR and it is
determined by wavelength, polarization, local incidence angle,
coverage of vegetation, roughness of terrain and so on. Now it
is very difficult to obtain accurate backscatter coefficient, so
some physical models are proposed through theory analysis
(Zhang, 2001), and some experiential formulas are also
proposed to fit the backscatter coefficient through surveyed
data in field. Our goal to simulate a SAR image is to ortho
rectify the SAR, so the texture and geometrical features are key
factors in order to match the simulated SAR with real SAR
image and the absolute gray-level value is not important,
therefore we use quadratic polynomial to calculate the gray-
level of SAR image based on the gradient of ground because
the gray-level of the SAR image correlates local incidence
angle while the local incidence angle correlates ground gradient.
The simulated image must be interpolated by neighbour DEM
grid points because the image of hillside toward the SAR side
look direction shrinks while that along the side look direction is
sparse because of undulation of terrain. Figure 1 shows the
simulated SAR image based on DEM and we can see that it is
very similar with the real SAR image in figure 2, so it is
possible and feasible to simulate SAR using DEM.
Figure 1. Simulated SAR image