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3.3 Single Photo Resection (SPR) 
The SPR method has fewer constraints on the bundles than the 
previous two methods. In this stability analysis procedure, the 
two bundles are allowed to have spatial and rotational offsets 
between their image coordinate systems. This approach, like the 
previous two methods, defines one grid in the image plane. The 
various distortions are removed from the grid vertices, and a 
bundle of light rays is defined for one set of IOP and grid 
vertices. This bundle of light rays is then intersected with an 
arbitrary object space to produce object space points. A single 
photo resection is then performed using the object space points 
in order to estimate the exterior orientation parameters of the 
second bundle. The variance component produced through this 
method represents the spatial offset between the distortion-free 
grid vertices as defined by the second IOP and the image 
coordinates computed through the back-projecting of the object 
space points onto the image plane (Figure 5). The IOP are 
deemed stable if the variance component is within the range of 
the variance of the image coordinate measurements. This 
similarity imposes no restrictions on the bundle position and 
rotation in space, and thus has similar constraints to those 
imposed by indirect georeferencing. Therefore, if the IOP sets 
are judged to be similar according to the SPR method, the 
relative quality of the object space that is reconstructed based 
on the indirect georeferencing technique using either IOP set, 
will also be similar. 
Figure 5: SPR method allows for spatial and rotational offsets between 
the two bundles to achieve the best fit at a given object space 
3.4 Comparing Equivalence of Different Distortion Models 
There exist several variations of distortion models that can be 
used to model lens distortion. The stability analysis tool can be 
used to evaluate the equivalence of different distortion models. 
This can be accomplished by calibrating the same dataset using 
different distortion models, and then comparing the output IOP. 
If the IOP produced using different distortion models are 
deemed to be similar, then the respective distortion models can 
be considered to be equivalent. Three different models were 
tested, and the results from these tests using real data are 
provided in the Experimental Results section of this paper. 
4. DEVELOPING MEANINGFUL STANDARDS 
Due to the various types of digital imaging systems, it is no 
longer feasible to have permanent calibration facilities run by a 
regulating body to perform the calibrations. The calibration 
process is now in the hands of the data providers, and thus the 
need for the development of standards and procedures for 
simple and effective digital camera calibration has emerged. 
Some digital imaging systems have not been created for the 
purpose of photogrammetric mapping, and thus their stability 
over time must also be investigated. These have been the 
observations of many governing bodies and map providers, and 
thus several efforts have begun to address this situation. The 
British Columbia Base Mapping and Geomatic Services 
established a Community of Practice involving experts from 
academia, mapping, photo interpretation, aerial triangulation, 
and digital image capture and system design to develop a set of 
specifications and procedures that would realize the objective of 
obtaining this calibration information and specify camera use in 
a cost effective manner while ensuring the continuing 
innovation in the field would be encouraged (BMGS, 2006). 
The developed methodologies will be utilized to constitute a 
framework for establishing standards and specifications for 
regulating the utilization of MFDC in mapping activities. These 
standards can be adopted by provincial and federal mapping 
agencies. 
The DPRG group at the University of Calgary, in collaboration 
with the BMGS, conducted a thorough investigation into the 
digital camera calibration process, where an in-door test site in 
BC was utilized as the test field. Through this collaboration, a 
three-tier system was established to categorize the various 
accuracy requirements, acknowledging that imagery will not be 
used for one sole application. The three broad categories in 
which these applications can be placed are the following: 
• Tier I: Category for very precise, high end mapping 
purposes. This would include large scale mapping in 
urban areas or engineering applications. Cameras 
used for this purpose require calibration. 
• Tier II: Category for mapping purposes in the area of 
resource applications (TRIM, inventory and the like). 
Cameras used for this purpose require calibration. 
• Tier III: This imagery would not be used for mapping 
or inventory. It is suitable for observation or 
reconnaissance but not for measurement. Cameras 
used for these purposes do not require calibration. 
Similar initiative between the United States Geological Survey 
(USGS), BMGS, and the Digital Photogrammetry Research 
Group is underway where the issues of camera calibration, 
stability analysis, and achievable accuracy are being 
investigated for the purpose of generating a North-American 
guideline for regulating the use of medium format digital 
cameras in mapping applications. 
4.1 Standards and Specifications for Digital Camera 
Calibration 
Through this joint research effort, some standards and 
specifications for acceptable accuracies when performing 
camera calibration were compiled and are as listed: 
1. Variance component of unit weight: 
• Tier I < 1 Pixel 
• Tier II < 1.5 Pixels 
• Tier III < N/A Pixels 
2. No correlation should exist among the estimated parameters 
3. Standard deviations of the estimated IOP parameters (xp, yp, 
c): 
• Tier I < 1 Pixel 
• Tier II < 1.5 Pixels