Full text: Proceedings, XXth congress (Part 8)

Yo) nd ES SEN, oM ims 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 
and is therefore very complex and time-consuming. Another 
disadvantage is that for every sensor type different model and 
different processing software has to be established. These 
reasons motivated the replacement of the physical sensor 
models by generalised models (Tao and Hu, 2001). 
In 1989 Kratky suggested as a generalised model the use of 
polynomial Rational Functions that.can support real time 
implementations and provide accurate solutions. The Rational 
Function model transforms the image pixel coordinates through 
the ratios of polynomial of ground coordinates. In this project 
Space Imaging Inc. provided the Rational Function coefficients 
(RFCs) used in the orthorectification process. 
3.2 The orthorectification processing 
Firstly the following input data were used to perform the 
— The RFCs provided by Space Imaging Inc. 
— The DTM that has a grid size of 25-m and covers all 
the study area 
— The GCPs obtained by GPS measurements and 
additional GCPs obtained by orthophotos of scale 1: 
5000 in order to cover evenly all the study area 
The orthorectification with these data resulted in a large RMS 
error of about 35 m. Aiming to minimise this error a 
methodology was developed involving the following tasks: 
— Synthesis from the two existing DTMs of a more 
accurate DTM 
- Refinement of the RFCs according to the ground 
coordinates of the GCPs 
—  Orthorectification separately in three parts of the 
image (the west, the east part of the city and the hilly 
3.2.1 Synthesis of DTM: In order to improve the accuracy 
of the DTM within all the study area the existing DTMs were 
mosaicked. Taking into account that the orthorectification of 
areas with intense anaglyph is usually problematic, it was 
considered necessary to use a highly accurate DTM in the hilly 
region. Thus in this specific part of the image it was preferable 
to use the DTM which covers this specific region and is 
characterized by a better accuracy. 
The process of mosaicking the DTMs consisted of three tasks. 
Initially, the hilly part was extracted from the DTM that covers 
all the study area. The extraction was made to the base of the 
mountain along points that were found to have about the same 
elevation in both DTMs. The second task involved changing the 
grid-size of the DTM of the hilly part (20 m) to fit the grid-size 
of the other DTM (25 m) through the process of resampling. It 
was also necessary to cut the DTM of the hilly part near the 
points mentioned above, so as to have a small overlapping with 
the other DTM. Finally, the DTMs were mosaicked and as for 
the overlapping area it was chosen to take the elevation values 
from the DTM of the hilly part, with the better accuracy. 
3.2.2 Refinement of the RFCs: The vendor-provided RF 
coefficients can be improved to provide a more accurate 
solution. Based on the known coordinates of the GCPs an affine 
transformation can be applied using as initial values the vendor- 
provided RFCs (Di et al., 2003). 
3.2.3  Orthorectification in three parts of the image: The 
orthorectification processing was applied three times for three 
parts of the image. Due to the fact that images with an intense 
anaglyph ~~ demand special attention during their 
orthorectification, it was preferable to process the hilly part 
separately. In order to have a good distribution of GCPs the 
image was also processed separately as far as the west and the 
east part were concerned. 
In this way three orthorectified image parts were produced 
which were finally joined together through mosaicking. The 
same methodology was carried out for both the panchromatic 
and the multispectral image and led to an improved accuracy of 
about 3.5 m. 
Image parts No. RMS 
Control Check Control Check 
West part 23 10 3.7m 3.1 m 
East part 51 15 3.9m 3.7m 
Hilly part 29 10 29m 29m 
Table 2. The number of points and RMS errors of the 
orthorectification of each part of the image 
3.3 The results of the orthorectification 
There are many factors that can influence the orthorectification 
processing and reduce the accuracy of the orthoimages. In this 
case the reasons can be found in the insufficient accuracy of the 
initial DTM, of the vendor-provided RFCs or in the different 
sources of GCPs (GPS and orthophotos). Using the 
methodology mentioned helped facing these problems and 
minimized the RMS error to a sufficient extend. 
In Table 3 the results of the orthorectification are listed 
according to the data being used and the great improvement of 
the accuracy is shown. 
Initial DTM Before the 35m 
After the 
Whole image 
Whole image | Synthetic DTM s 10m 
Three parts of Synthetic DTM After the 35m 
the image 
Table 3. RMS errors of the orthorectification according to the 
data used 
4.1 The fusion of images 
In 1999 Wald defined data fusion as a formal framework that 
expresses the means and tools for the alliance of data 
originating from different sources; it aims at obtaining 
information of greater quality; the exact definition of “greater 
quality” will depend upon the application. Image fusion aims at 
the generation of a single image from multiple image data for 
the extraction of information of higher quality (Pohl, 1999). 
Within this framework this project focused on a type of image 
fusion, the image sharpening. In image sharpening, higher 
spatial resolution panchromatic data is fused with lower spatial 

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.