Mularz, Stanislaw
aerial photographs and +0,5 data pixel for Landsat image
subsets. It is indicated a good geometric integrity of the data
used. After resampling procedures the remotely sensed
images (satellite and airborne) characterised a large (15x)
differences in spatial resolution (Figure 3.). Thus, a kernel
filter (15x15) have to be used to smooth the blocking
structure of the Landsat TM data (Figure 4.). Owning to the
kernel size the original DN values of Landsat TM band ware
preserved for panchromatic content from color aerial
photographs, IHS (Intensity, Hue, Saturation) tranformation M5 " "
procedure was performed and Intensity (Ie) as an equivalent Figure 4. Removing of the blocking structure from
of the spatial (panchromatic) information was taken for Landsat TM data
futher analysis. :
3.3 Merging procedures
A number of merging methods known from literature have been tested, namely: HPF (High Pass Filter), IHS (Intensity,
Hue, Saturation), PCA (Principal Component Analysis), SC (Spherical Coordinate), CN (Color Normalized), and
Cliche’s as well as Jaakkola’s procedures. For the final assessment of the merger usefulness for monitoring of an open-
cast mine area the HPF, IHS and PCA fusion formulas were chosen.
The HPF merger concept based on the high-frequency filtration of the image of the higher spatial resolution. The spatial
high pass filter removes most of the spectral information from airborne (panchromatic) data. The HPF results are added
(or substracted) — pixel by pixel to the lower spatial but higher spectral resolution images. This procedure indicating the
merger the spatial information of the higher spectral resolution data set (Chavez et al., 1991). In the HPF procedure one
can use different of the kernel size. In this study the kernel size of 31x31 pixels was used because of resolution ratio
(15:1) of Landsat TM and airborn data (after Chavez, 1991).
IHS is one of the most often used methods to integrate multisensor image data (Haydn et al., 1982; Welch and Ehlers,
1987; Carper et al., 1990; Grasso, 1993). With the IHS method, subsets of three selected Landsat TM band are first
transformed into the IHS domain. The panchromatic equivalent (Ie) of color aerial photographs as reference image was
then substituted of the Intensity component, and the data was transformed back to the red-green-blue (RGB) color
domain.
The PCA merging procedure is similar to that of the IHS method. Usually the six of the optical TM bands are used as
input to the PCA procedure. In this method transformation from the spectral space of the original TM bands is
performed to the new space of the principal components. As with the IHS formula histogram of the spatial
(panchromatic) data is stretched to be similar to the histogram of the first principal component, extracted from TM data.
The stretched image should have approximately the same variance and average as the first principal component. The
results of the stretched airborne data replaced the first principal component image, before the data are transformed back
into the original spectral space (Figure 5.). A spatial information is moved to all spectral bands after these data are
retransformed. Because the first principal component image will have the information common to all spectral bands
used, replacing the first principal component by airborne data (equivalent panchromatic band) is correct methodically.
Successfully use of PCA was reported by Chavez et al., 1991; Chavez and Kwarteng, 1989.
Figure 5. Fragment of the power plant area. Comparison of (Ie) equivalent of panchromatic image (left), (PC1) PCA
the first component (right). In the middle the difference of the two images
922 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.
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