Yong-Woong Lee
AN EXPERIMENTAL RESULTS ON THE REFINEMENT OF DEMS USING ITERATIVELY
GENERATED ORTHO-IMAGE FROM SPOT STEREOPAIRS
Yeu, Bock-Mo* , Lee, Yong-Woong**, Koh, Jin-Woo***, Cho, Bong-Whan ****
*
Professor, Yonsei University, Korea
Department of Civil Engineering
yeubm@yonsei.ac.kr
**,***
Senior Researcher,
****
Principal Researcher
Agency for Defense Development, Korea
lpllyw@sunam.kreonet.re.kr
xinu@sunam.kreonet.re.kr
bongwhan@sunam.kreonet.re.kr
Working Group IV/2
KEY WORDS: DEM, Iterative Orthoimage Refinement(IOR), Stereo Matching, Parallax, Digital Photogrammetry.
ABSTRACT
DEM generated by correlation matching may contain various sources of matching errors due to the geometric condition
and radiometric differences between the stereopairs. These errors may cause incorrect DEM. They also results in not
only degrading DEM accuracy, but also requiring correction during the post-processing of editing the mismatched parts.
Iterative orthoimage refinement (IOR) technique has been investigated mainly on the aerial photography to improve the
DEM generation and correction procedures. In this study, we developed and implemented IOR concept for SPOT
imagery. To do this, left and right orthoimages are generated using DEM and digital differential rectification from the
stereopairs. Iterative orthoimage matching was applied to calculate parallax which was used to correct elevation error.
Experiments are conducted to demonstrate the applicability of IOR for SPOT imagery. Three kinds of DEM have been
tested. The experimental results show that IOR can be effectively utilized for refining the SPOT derived DEM to
improve the procedure for DEM generation and to lessen the editing workload.
1 INTRODUCTION
Automatic DEM generation method has been widely implemented on the current digital photogrammetric workstation
systems. Comparing with the manual process, the digital approach has much benefits in producing DEM through the
digital correlation matching techniques. However, correlation method may contain many sources of matching errors if
the image has undetectable features, repeated micro structures, linear edges, and so on. Also these errors may arise
when the stereo images have different geometric and radiometric conditions. They results in not only degrading DEM
accuracy, but also requiring correction during the post-processing of editing the mismatched parts.
Since editing process of DEM is generally conducted by the operator with the computer or analytical plotter, it could be
labor-intensive job. So, an automatic error correction technique has been strongly desired to reduce the editing
workload in the digital photogrammetric workstation systems. Many studies relevant to DEM correction have been
mainly conducted to the aerial photography. In order to correct DEM effectively and quickly, Schenk(1989) proposed
the DEM generation using iteratively rectified images. Norvelle(1996) used Iterative Orthophoto Refinement(IOR)
approach to correct the elevation. Lobonc(1996) provided the theoretical background for elevation correction
computation and demonstrated the practical aspect of IOR using GDE DPW 750 for aerial photos. Since SPOT
imagery have different characteristics from aerial photos, some other approaches may be needed to accomplish DEM
correction. Especially, when a user wants to generate dense DEM(about 2 pixel post interval) using SPOT-P image, it is
difficult to effectively eliminate the blunders created during the correlation matching process.
In this study, we modified the aerial IOR concept and applied it to the SPOT imagery. To do this, left and right
orthoimages are generated from the stereopairs using DEM by digital differential rectification. Iterative orthoimage
matching is applied to calculate parallax which was used to correct elevation. Experiments are conducted on the test
site(part of SPOT GRS 305-277) to demonstrate the feasibility of IOR for the refinement of SPOT-derived DEM
through iteration.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
551
Yong-Woong Lee
2 IOR PROCESS
2.1 IOR Concept
IOR concept is based on the assumption that two(left and right) orthoimages generated from the same source of DEM
should be identical. Two orthoimages can be produced using the same DEM and the corresponding exterior orientation
parameters from the stereopairs. If the exterior orientation parameters are correctly estimated, elevation errors of DEM
may cause the geometric mismatches between the two orthoimages. The mismatches can be estimated from the parallax
through the matching of orthoimages.
To perform IOR, stereo images, exterior orientation parameters and DEM are required. Orthiomages are generated
firstly by applying DEM to each stereo image, then the conjugate points in stereo orthoimage were found by stereo
matching technique. The correction of elevation is computed by parallax between the two orthoimages. This process is
repeated until the parallax is smaller than the predetermined threshold. Figure 1 shows the procedure of DEM
refinement used in this study.
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Figure 1. Iterative DEM refinement procedure used in the study
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
Yong-Woong Lee
2.2 Orthoimage Generation
To generate the orthoimage by differential rectification, reference image and 3D modeling results(exterior orientation
parameters) and the DEM are used. Differential rectification can be done by the direct or indirect method dependent on
the direction of coordinate transformation. In this study, the indirect approach is used to make orthoimage shown in
Figure 2.
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2.3 Elevation Correction
The relationship between the matching error of the orthoimage and the error in DEM is shown in Figure 3. The parallax
is converted into height correction and used to estimate a new elevation. There are x and y parallaxes. However, if y
parallax is negligible, we can estimate the elevation from only the x parallax shown in equation (1).
dH ' = dX × ( H / B )
(1)
where,
d X = XR - X L
dH’ = estimated elevation to be corrected
H/B = baseline to height ratio
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
553
Yong-Woong Lee
sŒ› p”ˆŽŒ
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Figure 3. Relationship Between DEM and Orthoimage
Therefore new estimated ground coordinates are follows;
( XL, YL, ZL + dH ' ) = ( XL, YL, ZL + dX × ( H / B))
(2)
We iteratively update the elevation until the parallax is smaller than the predetermined threshold.
3
STUDY AREA AND DATA USED
Ý
Study area is 10km 10km in the ground. The
ground coverage of SPOT GRS 305-277 is
shown in Figure 4. The detail description of the
SPOT images used in the study are given in
Table 1. Three kinds of DEMs were generated to
conduct experiments, i.e., DEM_1 from the
DTED Level 1, DEM_2 from the left and
vertical image pairs of SPOT, and DEM_3 from
the left and right pairs of SPOT.
DEM_1 is used to investigate whether coarse
DEM can be refined into fine DEM through IOR
method. DEM_2 and DEM_3 are used to figure
out whether IOR can be applied to the same area
which has different geometric and radiometric
characteristics due to different acquisition date.
A reference DEM was created by the analytical
plotter using 1:30,000 aerial photography with
12.5m post interval.
Figure 4. Study area
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
Yong-Woong Lee
Left Image
Near Vertical
Right Image
Center latitude
36°22' 03"
36°22' 03"
36°22' 03"
Center longitude
127°11' 51"
127°17' 45"
127°15' 57"
Incidence angle
L22.7°
R08.6°
R26.9°
Acquisition date
1995. 4. 4
1995. 4. 5
1995. 1. 28
Image type
PAN/1A
PAN/1A
PAN/1A
Table 1. Characteristics of SPOT images used in the study
4 EXPERIMENTS
The positional accuracy of (refined) DEM is analyzed by covariance analysis using with reference DEM and also
RMSE on each DEM post is calculated. The parameters for covariance analysis and orthoimage matching are given in
Table 2. Three sets of stereo orthoimage are produced based on the DEM_1, DEM_2 and DEM_3. For each set the x
parallax is extracted to correct the each DEM. Results of applying iterative refinements are shown in Figure 5, 6 and 7.
We can easily see the distinct refinement. The refinement of each iteration process is also depicted in Figure 8, 9, and
10.
mask window size
search width
search height
threshold correlation value
Interval
covariance analysis
41 × 41
5
5
0.8
20/13
orthoimage matching
15 × 15
6
3
0.9
-
Table 2. Parameters for covariance analysis and orthoimage matching
Before IOR
After 1st IOR
After 2nd IOR
After 3rd IOR
Figure 5. The resultant DEM for each iteration(DEM_1)
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
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Yong-Woong Lee
Before IOR
After 1st IOR
Figure 6. The resultant DEM for each iteration(DEM_2)
Before IOR
After 1st IOR
Figure 7. The resultant DEM for each iteration(DEM_3)
As shown in Figure 8, 9 ,and 10, both horizontal and vertical accuracies are generally improved by IOR process. For
DEM_1, even though the standard deviations of easting and northing are decreased, their means are changed slightly.
On the other hand, height error goes down in mean and is changed little in standard deviation. Consequently, these
changes due to IOR iterations result in improving positional accuracy of DEM_1, horizontally and vertically.
The trends can be investigated by checking the pattern of parallaxes. Most parallaxes larger than 1 pixel are reduced
into smaller than 1 pixel. Considering the 3D modeling error about 10m, the resultant accuracy after IOR is considered
to be nearly approaching the modeling accuracy.
DEM_2 generated with SPOT L-V pairs showed the positional accuracy with CEP(Circular Error Probable of 90%)
20.8m and LEP(Linear Error Probable of 90%) 13.6m. DEM_2 has very good positional accuracy, therefore, the test
was focused on the possibility of refinement of small detail parts. Significant effects were not found by IOR if the
original quality of DEM is sufficiently good.
On the other hand, DEM_3 from SPOT L-R pairs showed worse positional accuracy than DEM_2, having CEP 32.35m
and LEP 17.4m. This poor accuracy is basically caused by bad geometric condition and radiometric inconsistency
between the stereopairs. The experimental results on DEM_3 shown in Figure 10 showed that IOR approach could be
applied to the stereoimages with bad matching conditions.
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
Yong-Woong Lee
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.
557
Yong-Woong Lee
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5 CONCLUSIONS
1) The accuracy and precision of SPOT derived DEM can be improved by applying IOR process. The possibility of
improvement was demonstrated by implementing IOR for SPOT-DEM and DTED-DEM.
2) IOR has a little effects on the improvement of the DEM quality, if the quality of original DEM is sufficiently good.
Actually, there are no significant changes in DEM quality by IOR for the DEM_2 which generated from the left and
vertical images of SPOT GRS 305-277.
3) If the stereoimages are acquired in long time separation, various errors may be included when image matching is
performed. In this case, IOR can be effectively used to improve the resultant DEM quality. Therefore IOR can be used
as a tool for correction and/or refinement of DEM which is generated automatically by digital photogrammetric process.
REFERENCES
Brockelbank, D.C., 1991. Stereo elevation determination techniques for SPOT imagery, PE&RS, Vol. 57, No. 8, pp.
1065-1073.
Clarke K.C., 1990. Analytical and Computer Cartography, Prentice Hall, pp. 206-210.
Lemmens, M.J., 1988. A survey on stereo matching techniques, IAPRS, Vol 27, Part 5, pp. 11-23.
Lobonc. T., 1996. Human Supervised Tools for Digital Photogrammetric Systems, Ph.D. Thesis, Purdue University
Novelle, F.R., 1996. Using iterative orthophoto refinement to generate and correct digital elevation models(DEM's),
ASPRS, Digital Potogrammetry, pp. 151-155.
Schenk, A.F., 1989. Determination of DEM using iteratively rectified images, Photogrammetry Technical Report No. 3,
Dept. of Geodetic Science and Surveying, The Ohio State University, Columbus, Ohio.
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B4. Amsterdam 2000.