  A new model-based image adjustment for the enhancement of multi-resolution
image fusion or pansharpening is proposed. Such image adjustment is needed for
most pansharpening methods using panchromatic band and/or intensity image
(calculated as a weighted sum of multispectral bands) as an input. Due various
reasons, e.g. calibration inaccuracies, usage of different sensors, input
images for pansharpening: low resolution multispectral image or more precisely
the calculated intensity image and high resolution panchromatic image may
differ in values of their physical properties, e.g. radiances or reflectances
depending on the processing level. But the same objects/classes in both images
should exhibit similar values or more generally similar statistics. Similarity
definition will depend on a particular application. For a successful fusion of
data from two sensors the energy balance between radiances/reflectances of both
sensors should hold. A virtual band is introduced to compensate for total
energy disbalance in different sensors. Its estimation consists of several
steps: first, weights for individual spectral bands are estimated in a low
resolution scale, where both multispectral and panchromatic images (low pass
filtered version) are available, then, the estimated virtual band is up-sampled
to a high scale and, finally, high resolution panchromatic band is corrected by
subtracting virtual band. This corrected panchromatic band is used instead of
original panchromatic image in the following pansharpening. It is shown, for
example, that the performance quality of component substitution based methods
can be increased significantly.
