Farhad Samadzadegan
Altogether we do not want to overrate the results of this first test with our new fuzzy reasoning approach for DTM
reconstruction. But with this experiments we could show that the developed method has the capability to acquire DT;
even in difficult terrain.
6 CONCLUSIONS
The goal of the presented work was to develop a new approach for DTM reconstruction based on fuzzy reasoning,
Fuzzy logic offers the theoretical framework on which processes of fuzzy nature can be build. Fuzzy inferens
processes allow to utilise a variety of constraints by formulating proper fuzzy rules. Corresponding algorithms for point
feature extraction and for matching have been developed and presented. These algorithms are embedded into an overall
process for DTM reconstruction
First experiments are carried out which show the applicability of the developed and implemented procedure. This first
success encourages to extend the fuzzy framework by including the object based reconstruction modules in fuzzy
inference processes. Some ideas about refining DTM generation by relating image feature extraction and surface
modelling are outlined in the paper. A detailed elaboration of the corresponding fuzzy rules are left for future work.
7 REFERENCES
Ackermann, F., Krzystek, P., 1991. MATCH-T: Automatic Mensuration of Digital Elevation Models, Proceedings of
Technical Seminar of the Sociedad Espanola de Catografia Fotogrametria y Teledetection. Barcelona, pp.67-73.
Ebner H., B. Hofmann-Wellenhof, P. ReiB, and F. Steidler, 1980. HIFI - A minicomputer program package for height
interpolation by finite elements, International Archive for Photogrammetry and Remote Sensing, Congress Hamburg,
Vol. 27(3), p. 205-215
Forstner, W., Giilch, E., 1987. A Fast Operator for Detection and Precise Location of Distinct Points, Corners and
center of Circular Features, Proceeding of ISPRS Intercommission Conference on Fast Processing of Photogrammetric
Data, Interlaken.
Hahn, M., 1989. Automatic Measurement of Digital Terrain Models by Means of Image Matching Techniques.
Proceedings of the 42" Phoogrammetric Week at Stuttgart University, p.141 — 151.
Huber, J.P., 1981. Robust Statistics, John Wiley & Sons.
Terzopoulos, D., 1986. Regularization of Inverse Visual Problems Involving Discontinuities, IEEE, Transaction on
Pattern Analysis and Machine Inteligence, Vol 4, p. 413-424.
Zadeh, L. A., 1965. Fuzzy Sets, Information and Control, Vol. 8, p. 338-353.
Zimmermann, H. —J., 1993. Fuzzy Set Theory, and Its Applications., Kluwer Academic Publishers.
806 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.
KEY
ABST
Mutu:
qualit
and €
(DTM
extrac
1
The u:
curren
times
data p
Additi
spatial
the an
Missi
will b
vantag
produ
optica.
areas.
the fie
On the
(e.g., 1
results
chance
In this
the em
concey
Model
buildir
the acl
2
Despit
an inte
izing t
means
° el
9 or
—