International Archives of Photogramme try and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999
construction of the viewing geometry during image acquisition.
It allows the correction of terrain induced distortions in case of
availability of a digital elevation model (DEM) (Cheng et al.,
1995).
Nevertheless, the combination of data with different spatial
resolution is of benefit for visual interpretation. In the case of
large spatial or spectral differences in images to be co-registered
the identification of features (lines or areas) leads to more
accurate results than the measurement of points only. The
information contributed by the two images facilitates the
extraction and identification of features. The human interpreter
is able to cope with slight misregistration.
In spectral terms, the fusion of panchromatic and multispectral
imagery does not invoke particular problems due to the similar
nature (visible and infrared spectrum) of the images involved.
This matter becomes more critical when fusing VIR and SAR.
The two image types are influenced by different effects both in
radiometry and geometry. The fusion of SAR/VIR does not
only result in the combination of disparate data but is also used
to spatially enhance the imagery involved (Welch, 1984). In
particular, the effect of speckle in SAR data has a strong impact
on the interpretability of the fused result. The application of
speckle filters is a trade-off between speckle reduction and loss
of detail.
5. RESOLUTION MERGE EXAMPLES AND
CONCLUSIONS
Image fusion is used in a broad variety of applications: geology,
land use / agriculture / forestry, change detection, map updating,
hazard monitoring, just to name a few. The possibility to
increase spatial resolution, whilst maintaining the important
information source of different spectral bands is of benefit for
most of these applications.
There are many publications containing suggestions on how to
fuse high resolution panchromatic images with lower resolution
multispectral data to obtain high resolution multispectral
imagery. Details can be found in Simard 2 (1982), Cliche et al.
(1985), Pradines (1986), Price (1987), Welch and Ehlers
(1987), Carper et al. (1990), Ehlers (1991), Mangolini et al.
(1993), Munechika et al. (1993) and Pellemans et al. (1993).
It has been shown that even the fusion of spatially very different
datasets can result in increased interpretability; an operational
example is the use of space photography and pushbroom
scanners, e.g. Russian imagery & SPOT XS (Pohl and Touron,
1999).
The resolution merge is one of the few generally accepted and
operational fusion techniques at pixel level. That becomes very
obvious from the availability of fused products from image
providers, as well as COTS package processing modules. The
fused products are suitable for visual interpretation and further
computer aided processing. The latter is reasonable only for
those techniques that result in radiometric values that are close
to the original input data (e.g. ARSIS).
New and planned satellite systems have already taken into
account the benefit of resolution merged products by launching
integrated sensor systems with different spatial resolution
sensors. Operational satellites are LANDSAT-7, SPOT-4, and
IRS-1C. ESA is also planning a multisensor, multiresolution
satellite called ENVISAT.
REFERENCES
Carper, W.J., Lillesand, T.M., and Kiefer, R.W., 1990. The use
of Intensity-Hue-Saturation transformations for merging SPOT
Panchromatic and multispectral image data. Photogrammetric
Engineering & Remote Sensing, 56(4), pp. 459-467.
Chavez, P.S., Sides, S.C., and Anderson, J.A., 1991.
Comparison of three different methods to merge multiresolution
and multispectral data: TM & SPOT Pan. Photogrammetric
Engineering & Remote Sensing, 57(3), pp. 295-303.
Cheng, P., Toutin, T. and Pohl, C., 1995. A comparison of
geometric models for multisource data fusion. In: Proceedings
of Geoinformatics '95 - International Symposium on ‘RS, GIS
& GPS in Sustainable Development & Environmental
Monitoring’, Hong Kong, pp. 11-17.
Chiesa, C.C., and Tyler, W.A., 1990. Data fusion of off-nadir
SPOT panchromatic images with other digital data sources. In:
Technical Papers 1990, ACSM-ASPRS Annual Convention,
Image Processing and Remote Sensing, 4, pp. 86-98.
Cliche, G., Bonn, F. and Teillet, P., 1985. Integration of the
SPOT Pan channel into its multispectral mode for image
sharpness enhancement. Photogrammetric Engineering &
Remote Sensing, 51(3), pp. 311-316.
Ehlers, M., 1991. Multisensor image fusion techniques in
remote sensing. ISPRS Journal of Photogrammetry & RS,
46(1), pp. 19-30.
Franklin, S.E. and Blodgett, C.F., 1993. An example of satellite
multisensor data fusion. Computers & Geoscience, 19(4), pp.
577-583.
Gillespie, A.R., Kahle, A. B. and Walker, R.E., 1986. Colour
enhancement of highly correlated images: I. Decorrelation and
HSI contrast stretches. Remote Sensing of Environment, 29(20),
pp. 209-235.
Hallada, W.A. and Cox, S., 1983. Image sharpening for mixed
spatial and spectral resolution satellite systems. Proc. of the
17th International Symposium on Remote Sensing of
Environment, 9-13 May, pp. 1023-1032.
2 Simulated data.
