The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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Sometimes we also need to determine the inverse 
transformation of Equation (1) from the GCPs set, which 
transforms the coordinate from (x i5 to (u i5 Vj). 
u = f~ l (x,y/a') 
v = g~\x,y/ß') 
The same procedure could be used to estimate the coefficients 
a’j and P’j of transformation (10). 
There are many challenges presented by global transformations 
that require consideration here. For global transformation 
models such as affine transformation, projective transformation, 
and global polynomial transformation, the parameters a and p 
are the same for all the points and are determined by all the 
control points, so a single function is used to model the 
transformation for each component of coordinates. When the 
geometric distortion is complex and location dependent, global 
models become inadequate to model the image geometry. 
Linear functions such as affine transformation and projective 
transformation are too simple to take the local variation into 
consideration. Nonlinear functions such as global polynomials 
use the least square methods to optimize the parameters, thus 
the local variation will be averaged across the whole image 
(Zitova and Flusser, 2003). Consequently, the registration error 
of locally deformed images by global functions is usually large 
and the spatial distribution of the error also varies with the 
location. 
3. RADARSAT-2 IMAGE GEOPROCESSING 
The basic product as generated by the RADARSAT-2 processor 
contains a Product Information File and one or more Image 
Pixel Data Files. The composition of RADARSAT-2 products 
is shown in Figure 1. All RADARSAT-2 products include one 
or more Image Pixel Data Files. One, two, or four Image Pixel 
Data Files may be included, corresponding to single, dual, or 
quad polarization modes, respectively. Each file contains the 
raster SAR image for a given polarization in GeoTIFF format 
(MDA, 2003). 
Figure 1: Product Composition 
The Product Information File is an ASCII file that logically 
groups known information on the product. For example, 
groupings are provided for source, image generation and 
imagery information related to the product. The Product 
Information File is encoded in Extensible Markup Language 
(XML) format as shown in Figure 2. 
All products (except RAW) are georeferenced, but not 
geocorrected. Since these products are not geographically 
corrected, the geographic metadata included in GeoTIFF is 
limited to the four comers tying image location to geographic 
location. GeoTIFF images are generated in TIFF strip format. 
Multi-polar images will be generated as separate GeoTIFF 
image files. All images are oriented such that north is nominally 
up and east is nominally on the right. 
A grid of tie points is included in the product.xml under the 
geolocationGrid node (highlighted in Figure 2), which ties the 
line/pixel positions in image coordinates to geographical 
latitude/longitude. The image coordinates are in units of pixels. 
The ground coordinates are latitude and longitude in units of 
decimal degrees. The ground coordinates are referenced to 
WGS-84, and pixel and line numbers start at 0. These grid tie 
points are used as Ground Control Points (GCP) to 
automatically geo-correct the image. 
xml 
B LJ product 
4? xmlns 
4* copyright 
4* xmlns:xsi 
4w xsi:schemaLocation 
E C product Id 
B 4» document Identifier 
S- _j source Attributes 
it imageGenerationParameters 
S' CJ imageAttributes 
+ C productFormat 
SB 4» outputMedialnter leaving 
B i '1 raster Attributes 
_J geographic Informat ion 
S '¿3 jgeoiocationGrid j 
B Ö rationalFunctions 
B Ö referenceEllipsoidParameters 
t Ö radiometric Informat ion 
+ radiometric Information 
E _J lookupTable 
B _3 lookupTable 
+ -3 lookupTable 
a Ö fullResolutionlmageData 
E- _j fullResolutionlmageData 
Figure 2: RADARSAT-2 Product XML Node Tree 
The Figure 3 and Figure 4 below give an example of 
RADARSAT-2 ScanSAR Wide dataset with image size of 
10508 x 10039 and pixel spacing and line spacing of 50 meters. 
The Figure 3 shows the GCP distribution in image coordinates 
and Figure 4 shows the GCP distribution in geographic 
coordinates. The GCPs are evenly distributed across the whole 
image.