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Least squares methods and some other related procedures
may give solution to an important group of problems of
photogrammetry and, generally, of survey and mapping, as
for example:
e network/block/joint adjustment;
© surface reconstruction, form descriptors;
e feature extraction and parsing;
e image/map/object matching.
Going further with the above said division of adjustment
and interpolation/approximation problems of photogram-
metry and, generally, of survey and mapping, first area col-
lects:
e on-line triangulation of images: spaceborne, airborne
and terrestrial;
e GPS data processing, automatic surveying (robotics).
Prior to processing, it should be pointed out pre-
processing of data collected by space photogrammetry tech-
niques (SPOT, MOMS, SAR, ...), with due care, as well as
in geodesy (e.g. GPS) and related sciences.
As far as interpolation and approximation are concerned,
one should remind a class of problems of photogrammetry
and cartography, related to:
e measurement devices (camera calibration and other
systems and sensors) and secondary effects;
e morphological features extraction, image/map/object
matching;
e DEM generation, orthoimage production and super-
imposition;
e image processing, analysis (classification) and under-
standing (semantic interpretation).
Note that these problems usually involve a large number
of observations and parameters and, consequently, require
the solution of large systems, i.e. systems with a large num-
ber of equations and unknowns. For these reasons, because
blunders, leverages and small outliers occur often in large
sets of data, robust procedures (robust estimators, reliabil-
ity analysis, ..) suitably provide for data preprocessing,
testing and archiving.
References
Ackermann F. (1979): The concept of reliability in aerial
triangulation. Ricerche di Geodesia Topografia e Fo-
togrammetria, n. 1, CLUP, Milano.
Baarda W. (1967): Statistical concepts in geodesy. Nether-
lands Geodetic Commission, new series, vol. 2, n. 4,
Delft.
Baarda W. (1968): A testing procedure for use in geodetic
networks. Netherlands Geodetic Commission, new series,
vol. 2, n. 5, Delft.
Barbarella M., Mussio L. (1985): A strategy for a ro-
bust identification of the outliers in the geodetic sciences.
Statistics and Decisions, supplement issue n. 2, pp. 397—-
405, R. Oldenbourg Verlag, Munich.
Benciolini B., Mussio L., Sansó F. (1982): An approach
to gross error detection more conservative than Baarda
snooping. Int. Archives of Photogrammetry, vol. XXIV,
part 3, pp. 41—59, Helsinki.
Bucciarelli B., Forlani G., Mussio L. (1992): Robust estima-
tion by using linear sequential algebra. Int. Archives of
Photogrammetry and Remote Sensing, vol. XXIX, part
B2, pp. 328-333, Washington D.C.
Draper N.R., Smith H. (1961): Applied regression analysis.
John Wiley & Sons, New York.
Golub G.H., van Loan C.F. (1986): Matrix computations.
North Oxford Academic, London.
Hampel F.R., Ronchetti E.M., Rousseeuw P.J., Stahel W.A.
(1986): Robust statistics. John Wiley & Sons, New York.
Huber P.J. (1981): Robust statistics. John Wiley & Sons,
New York.
Hawkins D.M. (1980): Identification of outliers. Chapman
and Hall, London.
Krarup T., Juhl J., Kubik K. (1980): Gétterdammerung
over least squares adjustment. Int. Archives of Pho-
togrammetry, vol. XXIII, part B3, pp. 369-378, Ham-
burg.
Forstner W. (1986): Final report on the joint test on gross
error detection of OEEPE and ISP WG III/1. OEEPE,
official publication n. 18, Frankfurt am Main.
Lawson C.L., Hanson R.J. (1974): Solving least squares
Problems. Prentice Hall, Englewood Cliffs (New Jersey).
Rousseeuw P.J., Leroy A.M. (1987): Robust regression and
outlier detection. John Wiley & Sons, New York.
Wicki F. (1992): Robuste ausgleichung geodätischer netze.
ETH-ZH, Inst. für Geodäsie und Photogrammetrie,
Bericht 189, Zurich.
Wicki F. (1992): Robuste M - schátzer und zuverlässigkeit.
ETH-ZH, Inst. für Geodäsie und Photogrammetrie,
Bericht 190, Zurich.
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B1. Vienna 1996