ipectral differences
• Saturation increase
tufmann 1985).
lputing and stretch
ssion via photowrite
i offers optimum
structural mapping
; optimization pro-
:ed image product,
I procedure the
evaluation results
e computer. Most of
re working pixel-
formation. The un
pixels with similar
ar example with the
re space as a cri-
The individual
class whose center
smaller than a
vised methods accu-
calculate the
ses before classi-
II pixels to one
be carried out using
The well known
example, is based
ihood with which
rs of these classes,
ed to the class with
AVIS, 1978). To get
criptions of the
n values in each
ix, are needed,
tistics training
ntroduced. The main
dures is the se-
e sample areas for
ds of classification
;upervised pro-
ir the classi-
escribe the
,s. A multispectral
latures for example,
;tural features as
le textural parame-
?ach pixel in a
.. Well known textu-
itistical evaluation
?n neighouring pixels
, 1973). The calcula-
jmeters for each of
jds to 7 additional
luent supervised
ion, with both the
jres, a highly so-
er channel combina-
out. Furthermore,
arocedure (WU, 1975)
jll information con-
jral channels in a
lassification of the
euclidean distance
ing channels 3/4.
ce (d=20 grey values)
11 be discriminated,
more spectral classes
tic Mapper data
te 7.7.1984) a small
ms to be a favourable
. Fig. 4 demonstrates
eads to more than 10
