Figure 4: Perspective view of Loess plateau's parallaxes
7 CONCLUSIONS
Array Relaxation for Multiple-point Least Squares Match-
ing (ARMLSM) has the great potential in the practical pho-
togrammetric systems due to its very high computational ef-
ficiency comparing with the traditional MLSM. The new for-
mulation of ARMLSM under the variable weight model pre-
sented by this paper makes it possible to capture the more
detailed terrains through the variable weight models which
are adjustable and followed the expected rule: giving tighter
constraint weights in flat open areas or poor image inten-
sity areas and looser constraint weights in rapid changed or
rich information areas. The preliminary experimental results
prove its ability to produce high-efficiency and high-quality
image matching on the general purpose computer, and the
results also show that very dense elevation models computed
by our ARMLSM provide the subtle terrain details. Since the
variable constraint weights can be applied in our ARMLSM, it
opens a new way for using efficient array algebra technique to
consider the breaklines, occlusions and discontinuity problems
during the matching processing. The strategy of choosing the
constraint weight discussed here is a very simple way, to find
a better solution for constraint weight models becomes our
current focus for the further developing of our ARMLSM.
8 ACKNOWLEDGEMENTS
| would like thank my colleague Maurice Friend for his reviews
of this paper.
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