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CURRENT DEVELOPMENTS 
It is significant that a growing number of research universities have 
acquired this system and are pursuing independent, but complementary 
approaches to the image matching/height determination problem, and to 
other related tasks, such as digital orthophoto production and feature 
analysis applications. Some of the other approaches to the image matching 
problem being pursued are based on the least squares method, while others 
are being based on concepts used in digital signal processing. Also being 
investigated is the task of integrating the image correlation system with 
a progressive sampling approach to point selection. 
Our own efforts are being directed toward increasing the accuracy, 
reliability, and speed of the current system, working within the framework 
of the DEM grid collection by the VLL method. Faster processors and faster 
video hardware are being considered. A current problem is what to do when 
cases of poor correlation are encountered while stepping through the grid 
of desired height points. It is believed that a solution should be sought 
on two levels: 
(1) Finding alternate sampling or computation strategies while the 
instrument is still at the point in question, to try and resolve 
the uncertainty while the image data is readily available, and 
(2) Finding a more global, system strategy of ways to prevent such 
occurrences in the first place. Determining how to efficiently 
utilize the machine and the operator in case manual re-observation 
is necessary, and deciding what data to record so that the point 
may be automatically interpolated later from surrounding points. 
With regard to item (1) it has been observed that on occasion the initial 
window size selected fails to include sufficient gray-level information to 
achieve good correlation. The system initially uses a small window of 
approximately 9 by 9 pixels, and a small delta-z range of around 50 
micrometers between the test levels (at photo scale). A sample image was 
chosen from 1:30,000 scale photographs with very little detail at the 
point to be measured. This small window yielded a very ambiguous 
correlation function as shown in Figure 1. Enlarging the window size to 
23 by 23 yields the correlation function shown in Figure 2. This curve 
shows more of a central tendency but the shape is still insufficient to 
determine a peak, or maximum point. Maintaining the 23 by 23 matrix but 
increasing the pixel spacing to 150 micrameters yields the curve shown in 
Figure 3. Utilizing a window matrix of 125(x) by 3(y) yields the curve 
shown in Figure 4. Thus even though there may be insufficient image detail 
at the point in question, there may be such detail (gray-level 
modulations, edges, etc.) close by. A program should have the flexibility 
to utilize such a dynamic windowing capability in order to obtain the 
required levels of information necessary for image matching. 
Another area from the same pair of photographs was selected in which the 
information content was much higher. This yielded the curve shown in 
Figure 5 for the 9 by 9 window, and the curve in Figure 6 for the 
23 by 23 window. Both of these curves display a well defined peak in the 
region of no parallax. 
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