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ACCURACY IMPROVEMENT IN COMPUTATIONAL CLOSE-RANGE PHOTOGRAMMETRY BY THE USE OF MULTI-CONTROL VARIABLE {NCV)
MONTE CARLO METHOD
H.N.Nagaraja, Assoc Professor, University of Zimbabwe, Zimbabwe
Commission V, worhing group V/7
KEY WORDS:
ABSTRACT
Statistics, Application, Simulation, Error, Accuracy, Ciose-Menge, Method,
Accuracy improvement hy use of multi-conirol variate method MCV} among other Monte Carlo methode is presented,
The INCV) method is particularly applicable in close-range photogrammetry as the accuracy of computed three
dimensional coordinates of any detail point can be improved by the sisultanecus comparison and rontideralion of
à set of all available object space control point coordinates.
1. INTRODUCTION
Monte Carlo techniques are often used in many
scientific and other disciplines and an isportant
part nf this effort is direried towards variance
reduction in systems analyses, The applicability of
some of these techniques to the normal case of
terrestrial and close-range photogramseiry has been
identified, developed and partly demonstrated in
iNagaraja,1971,92), Though at first sicht it might
seen that sampling procedures only apply in case of
simulation studies, further reflection should
indicate that conceptually and practically, it should
be possible to incorporate these ideas in reduction
of variante while dealing with practical data.
However, this paper deals with à case study involving
some data sets obtained by simulation only, yet
closely conforming to actual data. It was not
possible to use live or field dats in this study,
The subject of variance reduction has received,
outside photogrammetry, considerable attention and a
number nf methods have been developed. Hence, there
ère à few techniques that help to intreasp accuracy
any hence efficiency of simulations, — sometimes
substantially, by producing less variable
übservations, Accordingly, there is a need to study
such sethods and possibilities,
Applications of tigulation are net ne in
photograsmetry — hut new applications are still
possible. Variance reduction techniques seek either
increase in precision {decreased variance) for a
399
fixed sample size of m Decresse in sample Size
required to oblain a given degree of precision,
Several authors have cautioned us in using these
techniques without first ensuring their applicability
and effectiveness, 1f properly used, these
technigues ran provige tremendous increase in the
efficiency of the sodel; however, if the intuition is
faulty and the analyst does mel use a reasonable
design, the technique can also be quite unpredictable
and perhaps actually increase variante for 5pae
techniques, Because of this charatterislit reason, a
systematic and thorough study of the selected method
is both desirable snd essential in adapting it for
any specific application in photograsmetry,
The multi-control varisbies technique applies very
weil when there tiose repetition or a near
equivalent to the process we arp using in simulating
that can be treated theoretically, Thus, in the
normal case of clpse-range phologramsetry, Just as
alep in aerial pholograssetry, we have an equivalence
between cosputation of three disencional coordinates
of 8 non-controi object space point and that of à
given or knows control object Space point. We can
then simulate the least acturate Y-Coordinates isay,
when it is known that the Y-coordinate axis and
Camera — axis are parsllell cof a selected object
space point and that of the known control point
sisultanenusly, using sa&bP random nusber Stresss in
both computations, The difference in the known and
computed coordinate of the contro! object space
point is indeed an estimate nf the correction thet
tan be conveniently applied to the computes
coordinate nf the selected non-control chiert space
PE 8
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B5. Vienna 1996