2.3 Typical Adjustment Results 
Over the last several years there have been several 
projects which have had sufficient ground control points 
to establish a level of confidence in the reliability of the 
adjustment processing. It has been found in most cases 
that the RMS residual control point errors after the ad 
justment are at the magnitude of the pixel resolution. 
Also, the RMS intersection errors for the stereo conjugate 
points are usually less than the pixel resolution (Gibson, 
1987). These figures can vary depending on the resolu 
tion of the imagery and on the quality of the ground con 
trol coordinates. For example, if the uncertainty in the 
control point coordinates derived from maps (typically 
1:10000 or 1:20000 scale), is greater than the pixel reso 
lution, it has been found that the residual errors from the 
adjustment tend to reflect the errors in the control point 
coordinates rather than the pixel resolution. 
3 Ortho-image Generation 
One of the desired end-products from the geometric cor 
rection processing has been mosaiced ortho-images. It 
has been possible to demonstrate that such products may 
be generated with relative ease and without requiring hu 
man intervention to stitch overlapping strips of imagery 
together. 
3.1 Terrain Height Correction 
One of the necessary elements for the production of ortho- 
images is accurate terrain height data and the ability to 
incorporate that data into the image resampling process. 
The terrain height information is incorporated into the 
resampling algorithm by computing the intersection of 
the pixel pointing vector (zj or xl in Figure 1) for each 
pixel with the surface of the earth which in this case is 
represented by a digital elevation model. The intersection 
calculations are iterative, based on estimating a scale fac 
tor for the pointing vector to extend it to the intersection 
point. The scale factor is initialized as the difference be 
tween the flying height and the average terrain height, 
normalized for a unit focal length lens. The elements of 
the pointing vector are multiplied by the scale factor and 
the coordinates of the vector are computed. The height 
component of the vector coordinates is compared with 
the terrain height value for the same horizontal location. 
The scale factor is then adjusted based on the ratio of 
the height difference and the original normalized flying 
height. Once the algorithm has been initialized in this 
fashion for each scan line of imagery, the scale factor may 
be passed from pixel to pixel with only minor corrections 
needed for each. Figure 2 shows the results of comput 
ing two ortho-image products and then merging them to 
gether in the common overlap region with a simple linear 
weighting algorithm. The details of the imagery sample 
are as follows: 
• The imagery covers 2 km by 2 km of Cambridge, 
Ontario. 
• The flying height was 1400 metres which resulted in 
a ground resolution of 1 metre. 
• The overlap region of the two flight lines is approx 
imately 100 metres wide. The extent of each of the 
separate images is indicated in Figure 2. 
• The terrain height variation in the area covered has 
a range of 40 metres. The misregistration between 
the images for this amount of height variation would 
have been up to 28 metres if the terrain height cor 
rection had not been applied. 
• The terrain height data was supplied by the On 
tario Ministry of Natural Resources as spot eleva 
tions which were subsequently interpolated to a reg 
ular grid for the use in the resampling processing. 
• The two input images were radiometrically balanced 
and adjusted to have the same average intensities 
before they were combined. This was done by a sim 
ple empirical method of deriving a scale factor and 
an offset function which varies across each image to 
adjust the radiometric histograms to have matching 
statistics. 
The imagery was generated as part of a project sponsored 
by the Ontario Centre for Remote Sensing (OCRS) while 
the authors were employed by Rem/Sense Mapping Tech 
nologies Inc.,(R/SMT), (R/SMT, 1989). An initial check 
of the quality of the corrected imagery was performed by 
overlaying the Ontario 1:10000 base map of the area. A 
good agreement of features was noted and it was imme 
diately obvious where new features existed that were not 
present on the map, however a more formal evaluation 
which was to follow has not been completed. 
3.2 Further Development 
Although on the surface, the combined imagery appears 
to look seamless, there are several areas where there is 
some blurring of features in the region of overlap. This 
is partially due to the fact that the terrain height data 
was obtained from another source and also that it did 
not contain data for ground cover or buildings. It is felt 
that the best results in generating ortho-images will be 
obtained when they are computed using terrain height 
derived from the MEIS imagery itself so that there will 
be a greater degree of consistency between the features in 
the imagery and in the terrain height data. The current 
software effort for MEIS imagery is therefore centered on 
the development and refinement of an automated terrain 
height extraction package using the forward and aft stereo 
channels of MEIS. The software is being developed on a 
computer graphics workstation in order to facilitate the 
rapid display of both imagery and derived height prod 
ucts. One of the key features of the system will be a