The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
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alternate, application oriented, color space to represent
multispectral data more objectively (Nasr et al., 2001). It uses
three positional parameters in lieu of the Red, Green and Blue
(RGB); Intensity, Hue and Saturation. Intensity relates to the
overall brightness of a color or energy level of the light and is
devoid of any color content. It shows how close it is to black or
white. Hue refers to the dominant or average wavelength of
light contributing to a color, i.e. the actual perceived color such
as red, blue, yellow, orange, etc. Saturation specifies the degree
to which the color is pure from white light (grayscale) dilution
or pollution. It runs from neutral gray through pastel to
saturated colors. The transformation from RGB color space to
IHS space is nonlinear, lossless and reversible. One can vary
each of the IHS components without affecting the others. It is
performed by a rotation of axis from the first orthogonal RGB
system to a new orthogonal IHS system. The equations
describing the transformation to the IHS are as follows
(Pellemans, et al., 1993):
VI
vi
0
r
1
VI
0
y
. VI _l 0
VI VI u
0 0 1
WI
r ^ o 10 r
VI J
G
R
The value of H, S and I can then be computed as:
H = tan
S = cos'
fP
Vx,
4~y
V
x + y + z
' <t> (tf)
l-(x + y + z)l I m (H ,S)
Where is the maximum co-latitude permitted at a
given hue and / (//, S) is the maximum intensity permitted
at a given hue and co-latitude.
3. DATA ACQUISITION AND METHODOLOGY
To aid the extraction of the information by visual interpretation,
data fusion is used to provide a new refined image and
contribute to a better understanding of the objects observed
within that image. Fusion of different imaging sensors data
involves two major steps. First, the digital images from both
sensors are geometrically registered in respect to one another.
Next, the information contents (spatial and spectral) are mixed
to generate a single data set that contains the best of both sets
(Eldougdoug and Nasr, 1994). The geometric registration plays
an essential role because misregistration causes artificial
features in the multisensor data sets, which falsify the
interpretation later on. It includes the resampling of image data
to a common pixel spacing and map projection (Onsi, 2002).
The study area covers approximately 30.8 km by 45.4 km as
shown in the location map (Figure 1). Two sets of multisensor
data are used in this study. Part of landsat TM scene (Path: 177,
Row: 45) 28.5 m resolution, acquired on October, 1984 (Figure
2) and part of RADARSAT-1 scene, 12.5 m resolution,
acquired on September, 1998 (Figure 3). These images were
processed using the ERDAS Imagine, version 8.7 software. IHS
method is applied to three bands at a time, whose fusion output
is displayed in either true or false color. Therefore, three
selected bands from the Landsat scene; 7 (2.08 - 2.35 pm), 4
(0.76 - 0.90 pm) and 2 (0.52 - 0.60 pm) were used since they
contain most of the information about the surface geological
features of the study area.
26° E 29° E 32° E 35° E
Figure 1. Figure placement and numbering
Figure 1. Location map of the study area indicated by hatches
in a rectangular form
Figure 2. Landsat TM scene, October 1984