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3. TEST AND RESULTS
3.1 Test with aerial Photos of Mountainous Area
The algorithm has been tested with four aerial photos of Tapan Alps area (Figure 2). The test consists of four stages. In
the first stage, relative orientation parameters between the first pair of image were calculated by observing some match-
ing point coordinates. Then DSM based orientation was done on the first pair with 7 degrees of freedom under epipolar
geometry restriction. After that, the orientation parameters of the third image were optimized by performing the algo-
rithm on the second pair with the parameters of the second image fixed. Similarly the parameters of the 4th image can be
computed. Digital elevation model of Japan Alps mountain area published by Geographical Survey Institute (50m mesh)
was used in this test.
Ist pair 2nd pair 3rd pair
LL | 1
2nd image
Ist image 3rd image 4th image
DL qu
] relative orientation
2.DSM based orientation |
3. DSM based orientation
b ie 4. DSM based orientation
Figure 2. Flow of theTest
Figure 3 illustrates the process of the optimization of the third pair with 6 degrees of freedom. The second image row of
the figure shows that difference of the two images is minimized through optimization. Figure 4 shows a mosaic image of
orthophoto created with resultant orientation parameters and the DEM.
Before Optimization After Optimization
Mean of Two Images
Difference of Two Images
Figure 3. Optimization process of DSM Based Orientation
3.2 Precision of Orientation
The precision of the algorithm largely depends on resolution of DSM. Figure 5 shows the relationship between DSM and
precision of orientation. Precision of the orientation is measured by computing mean GCP error at six GCP points. The
tests resulted that the mean error is almost 1/2 or less than the resolution of DSM. This shows that precision of this
method is better than resolution of original surface model.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 655