6. SYSTEM VERIFICATION
6.4 Image Spatial Accuracy Assessment
6.4.5 Photogrammetric process
Figure 28: Example of perspective distortion between two images from different flight lines.
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5) Initial X and Y coordinates for the photo stations were input from the spreadsheet provided. The rotation angles for tip, roll and yaw were set as zero.
6) The automated tie point matching utility of Orthobase was run. This utility uses image processing algorithms to find corresponding points in overlapping images.
It was found during step 6 that the software was unable to fmd tie points between the images automatically. This was due in part to the inaccuracy of the initial photo station coordinates provided. After analysis of the process by which the approximate photo stations were determined it was calculated that at the flying height of 2530m AOL and for a tip or roll of 5°, these coordinates would have been incorrect by more than 220m. The images only covered an average area of 1250m by 830m and an error of 220m was therefore significant and accounted for the software's inability to automatically find tie points. Ifit had been possible to save the photo station
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coordinates that were output by the Trimble Pro-XRS unit during the test flight then Craigie (2000) believed that the auto-tie point functionality would have worked. Craigie (2000) has successfully processed scanned air photographs using GPS photo station coordinates without any problems which would indicate that the same would be possible if digital camera imagery was used. However, Craigie (2000) emphasised that the accuracy ofthe auto tie point matching would also depend on the variation of the pitch and roll angles between consecutive photographs being small. Orthobase uses the input data to calculate the approximate location offeature points on the overlapping areas of multiple images. Once an approximate location has been defined, Orthobase uses a pixel search window to search for the exact image position in neighbouring images. The size of the search window can be defined by the user and is 21 x 21 pixels by default. This would equate to an approximate search window size of 13m x 13m on the ground for the digital camera imagery captured in the test flight. If there are large changes in the tip and roll angles from one image to the next then the location of feature points in neighbouring images will be poorly approximated and tie points may not be found. A much larger search window could be defined to allow for large tip and roll angles, but this would dramatically increase the computer processing power and time required to achieve a solution.
Furthermore, the heading (yaw) of the aircraft should be known and should vary by less than 2 degrees from frame to frame (Craigie, 2000). The yaw was not measured or accounted for during the flight and an analysis ofthe results of the bundle block adjustment subsequently performed and documented in section 6.4.6 indicated that the variation in the yaw was in excess of 2 degrees between some of the photos. This would account in part for the software's inability to perform the auto tie point matching routine. Furthermore, the difference in the tip and roll angles between certain consecutive images was in excess of 7 and 10 degrees, respectively. These high pitch and roll angle variations, together with the unavailability of accurate photo station coordinates and yaw measurements, contributed to the failure of the auto tie point process. The need to measure or account for tip, roll and yaw of the aircraft was therefore identified as a future requirement in order to achieve optimal automation of the post-flight image rectification procedure. A sensor, such as an Inertial Navigation System (INS) or cheaper tip/roll sensor, would need to be incorporated into the in-flight system to measure the tip, roll and yaw in real time. As previously discussed, no suitable low cost sensor with sufficient sensitivity and accuracy was found during
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the research phase of this project.
Due to the auto tie point process failing, the tie points were identified manually. This resulted in far fewer tie points being identified and used in the bundle block adjustment than if the tie point matching had been automated. Only 33 tie points were identified and used in the bundle block adjustment, whereas the number of tie points could have been increased to 500 points per image with very little increase in processing time if the process had been automated (Craigie, 2000).
Having fewer tie points reduced the connectivity between the images in the block and was likely to reduce the quality of the triangulation solution, in other words, reduce the spatial accuracy of the orthophotos produced. The increase in accuracy with an increase in tie points can be attributed to the increase in data redundancy, thus allowing for the minimization and distribution of error throughout the photogrammetric network of observations (Erdas, 1999). Since GIMS had never worked with digital camera images before, the likely reduction in spatial accuracy due to having fewer tie points could not be estimated.
A possibility which was not explored in this project was to use the photo station coordinates and tip, roll and yaw angle results from the bundle block adjustment described above as initial estimates of the photo station coordinates and tip, roll and yaw angles of each image in a second bundle block adjustment using the auto tie point functionality ofOrthobase. While repeating the bundle block adjustment procedure would require additional time and increase costs, these initial results would be sufficiently accurate to ensure that the auto tie point matching would work for a second block adjustment (Craigie, 2000). The GCPs measured in the initial run could be saved and used as input into the second run. The increase in the spatial accuracy of the results of the bundle block adjustment using auto tie point matching could also be sufficient to offset the extra cost and time of repeating the bundle block adjustment. Ifa low cost sensor to measure tip, roll and yaw in real time is not found then this approach would have to be investigated further.
Obviously, the need to repeat the bundle block adjustment would depend on whether higher accuracy imagery than could be obtained from an initial bundle block adjustment with manually defined tie points was required for a particular application.
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The results of the bundle block adjustment using the manually defined image tie points are presented and discussed in the following section.