Many image fusion algorithms such as Principal Component Analysis (PCA), Multiplicative Transform, Brovey Transform, IHS Transform and wavelet transform have been presented in order to fuse low-resolution multispectral data with high-resolution panchromatic data.
More recently Yun Zhang has presented a new algorithm for the fusion of Landsat ETM and Ikonos data respectively. In this study we compare the efficiency of five of the above fusion techniques and more especially the efficiency of PCA, Multiplicative Transform, Brovey Transform, IHS Transform and Pansharp for the fusion of Landsat ETM data. The area of interest is situated in Western Peloponnese near the city of Pyrgos. The broader region combines at the same time the characteristics of an urban, a coastal and a rural area. A Landsat 7 ETM cloud free subscene taken in the morning of July 28, 1999, was used in this comparative study. For each fused image we have examined: a) the optical qualitative result, b) the statistical parameters of the histograms of the various frequency bands, especially the standard deviation c) the amplitude spectrums of the frequency bands. All the fusion techniques improve the resolution and the optical result but according to the statistical analysis the Brovey and the Multiplicative techniques do not improve the contained information in the fused images. The IHS fusion technique seems to have the best optical result, increases the sum of the contained information but provoke changes to the colors of the original RGB image. The PCA fusion technique seems better in discriminating between the coastal zone, the urban area and the rural area and maintains the natural colors. The Pansharp fusion technique gives the best results without changing at all the statistical parameters of the original multispectral image.