spectral values are also well preserved. For complete details see Rosso et al. (2009).
TerraSAR-X’s capability of depicting features with certain structural characteristics
may be of great value, for example, after a catastrophe where structural damage
occurs. High-resolution radar images may not be able to show exactly what the
damaged structures are but would clearly show if the structural characteristics are
extensively modified. These advantages of radar over optical data are more evident as
the resolution of the EO images decreases.
2.6 CONCLUSION
It is safe to conclude that iconic image fusion techniques can be used to overcome
scale differences in multisensor remote sensing. It has to be noted, however, that for
multisensor, multidate fusion spectral characteristic methods such as Ehlers fusion
have to be applied so that the multispectral information can still be correctly analyzed.
Our results indicate that for EO fusion scale ratios of 1 : 2 to 1 : 10 seem to be the
reasonable range. This is very much in line with the findings reported by Ling et al.
(2007b). For radar/EO image fusion, on the other hand, sensible scale ratios range
from 1 : 6 to 1 : 20. For scale ratios outside these specified ranges, only noniconic
fusion techniques such as feature-based (symbolic) or decision-based fusion techniques should be applied (Pohl and van Genderen, 1998).
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 and Remote Sensing 56(4):459–467.
Chavez, W. J., Sides, S. C., and Anderson, J. A. 1991. Comparison of three different methods to
merge multiresolution and multispectral data: TM & Spot Pan. Photogrammetric Engineering and Remote Sensing 57(3):295–303.
Cliche, G., Bonn, F., and Teillet, P. 1985. Integration of the SPOT pan channel into its
multispectral mode for image sharpness enhancement. Photogrammetric Engineering and
Remote Sensing 51(3):311–316.
Edwards, G., and Jeansoulin, R. 2004. Data fusion - from a logic perspective with a view to
implementation, Guest Editorial. International Journal of Geographical Information
Science 18(4):303–307.
Ehlers, M. 1991. Multisensor image fusion techniques in remote sensing. ISPRS Journal of
Photogrammetry and Remote Sensing 46(1):19–30.
Ehlers, M. 2004. Spectral characteristics preserving image fusion based on Fourier domain
filtering. In M. Ehlers, F. Posa, H. J. Kaufmann, U. Michel and G.De Carolis (Eds.), Remote
Sensing for Environmental Monitoring, GIS Applications, and Geology IV, Proceedings of
SPIE, 5574, Bellingham, WA: 1–13.
Ehlers, M., and Klonus, S. 2004. Erhalt der spektralen Charakteristika bei der Bildfusion durch FFT
basierte Filterung. Photogrammetrie-Fernerkundung-Geoinformation (PFG) 6:495–506.
REFERENCES
31
TerraSAR-X’s capability of depicting features with certain structural characteristics
may be of great value, for example, after a catastrophe where structural damage
occurs. High-resolution radar images may not be able to show exactly what the
damaged structures are but would clearly show if the structural characteristics are
extensively modified. These advantages of radar over optical data are more evident as
the resolution of the EO images decreases.
2.6 CONCLUSION
It is safe to conclude that iconic image fusion techniques can be used to overcome
scale differences in multisensor remote sensing. It has to be noted, however, that for
multisensor, multidate fusion spectral characteristic methods such as Ehlers fusion
have to be applied so that the multispectral information can still be correctly analyzed.
Our results indicate that for EO fusion scale ratios of 1 : 2 to 1 : 10 seem to be the
reasonable range. This is very much in line with the findings reported by Ling et al.
(2007b). For radar/EO image fusion, on the other hand, sensible scale ratios range
from 1 : 6 to 1 : 20. For scale ratios outside these specified ranges, only noniconic
fusion techniques such as feature-based (symbolic) or decision-based fusion techniques should be applied (Pohl and van Genderen, 1998).
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 and Remote Sensing 56(4):459–467.
Chavez, W. J., Sides, S. C., and Anderson, J. A. 1991. Comparison of three different methods to
merge multiresolution and multispectral data: TM & Spot Pan. Photogrammetric Engineering and Remote Sensing 57(3):295–303.
Cliche, G., Bonn, F., and Teillet, P. 1985. Integration of the SPOT pan channel into its
multispectral mode for image sharpness enhancement. Photogrammetric Engineering and
Remote Sensing 51(3):311–316.
Edwards, G., and Jeansoulin, R. 2004. Data fusion - from a logic perspective with a view to
implementation, Guest Editorial. International Journal of Geographical Information
Science 18(4):303–307.
Ehlers, M. 1991. Multisensor image fusion techniques in remote sensing. ISPRS Journal of
Photogrammetry and Remote Sensing 46(1):19–30.
Ehlers, M. 2004. Spectral characteristics preserving image fusion based on Fourier domain
filtering. In M. Ehlers, F. Posa, H. J. Kaufmann, U. Michel and G.De Carolis (Eds.), Remote
Sensing for Environmental Monitoring, GIS Applications, and Geology IV, Proceedings of
SPIE, 5574, Bellingham, WA: 1–13.
Ehlers, M., and Klonus, S. 2004. Erhalt der spektralen Charakteristika bei der Bildfusion durch FFT
basierte Filterung. Photogrammetrie-Fernerkundung-Geoinformation (PFG) 6:495–506.
REFERENCES
31