The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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Figure 6. Spectral analysis of fused images 
Amarsaikhan, D. and Douglas, T.,2004. Data fusion and 
multisource image classification. International Journal of 
Remote Sensing, 10 September, vol. 25, no. 17, pp. 3529-3539. 
Aschbacher, J., and Lichtenegger, J., 1990. Complementary 
nature of SAR and optical data: a case study in the Tropics. 
Earth Observation Quarterly, vol.31, pp.4-8. 
Bethune, S., Muller, F., Donnay, J.P.,1998. Fusion of 
multispectral and panchromatic images by local mean and 
variance matching filtering techniques. Fusion of Earth Data, 
Sophia Antipolis, France, 28-30 Jan 1998. 
Binh, D., T., Christiane, W., Aziz, S., Dominique, B., VanCu, 
P.,2006. Data fusion and texture-direction analyses for urban 
studies in Vietnam. 1st EARSeL Workshop of the SIG Urban 
Remote Sensing Humboldt Universität zu Berlin, 2-3 March 
2006. 
Colditz, R., R., Wehrmann, T, Bachmann, M, Steinnocher, K, 
Schmidt, M, Strunz, G and Dech S,2006. Influence of image 
fusion approaches on classification accuracy: a case study. 
International Journal of Remote Sensing, vol. 27, No. 15, 10 
August 2006, pp. 3311-3335. 
Jin, Y., Ruliang, Y. and Ruohong, H,2006.Pixel level fusion for 
multiple SAR images using PCA and wavelet transform. Radar, 
2006. CIE '06. International Conference, pp. 1-4, Oct. 2006. 
Li, S. and Wang, Y.,2001. Discrete multiwavelet transform 
method to fusing Landsat-7 panchromatic image and multi 
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1962- 1964. 
4. CONCLUSIONS 
Liu, J. G.,2000. Smoothing Filter-based intensity modulation: a 
spectral preserve image fusion technique for improving spatial 
details. International Journal of Remote Sensing, vol. 21, pp. 
3461-3472. 
The aim of this study is to select the best fused images and 
making the comparisons between the SAR components of 
fusion process. To see the impacts of penetration only, SAR 
images (RADARSAT and PALSAR) were chosen with the 
same polarisation but with the different bands (C band and L 
band). The results show that HPF and DWT give the similar 
quality and quantity for both RADARSAT and PALSAR fused 
images. IHS gave the worst results. For the agricultural areas 
using HPF for PALSAR-SPOT fusion gave the best spectral 
results. 
Pal, S.K., Majumdar, T. J., Bhattacharya, A. K.,2007. ERS-2 
SAR and IRS-1C LISS III data fusion: A PCA approach to 
improve remote sensing based geological interpretation. ISPRS 
Journal of Photogrammetry & Remote Sensing, vol.61, no. 5 pp. 
281-297. 
Pohl, C., and van Genderen, J.L., 1998. Multisensor image 
fusion in remote sensing: concepts, methods and applications. 
International Journal of Remote Sensing, vol. 19, no.5, pp.823- 
854, Mar. 1998. 
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