Efficient intensity-hue-saturation-based image fusion with saturation compensation

The intensity-hue-saturation (IHS) and Brovey transforms are two widespread image fusion methods in the remote sensing community. However, both are sensitive to the characteristics of the analyzed area. Restated, they often face color distortion problems with fused images. This work investigates models representing the color space in images. Schemes governing saturation change during fusion are also evaluated to derive the correct saturation values for each pixel in a fused image. In addition, algorithms that compensate distorted saturation values for distinct image fusion methods are derived and discussed. Methods to extend current image fusion methods to any arbitrary order are also outlined. Finally, an illustrative example of a fused SPOT image demonstrates the color distortion problem while an IKONOS image is adopted to evaluate various contemporary image fusion methods.