In many image processing applications the image quality
should be improved to support the human perception.
The image quality evaluation by the human observers is,
however, heavily subjective in the nature. Different
observers judge the image quality differently. In many
cases the relevant part of image information which is
perceived by the observer should reach a maximum. In
this work we present a new approach to image
enhancement which is based on fusion of different
algorithms. We use fuzzy measure theory to represent the
human subjectivity, and fuzzy integrals to aggregate this
subjectivity with objective criteria. We also apply the
Dempster aggregation rule to define a degree of
compromise. Finally, we use a fuzzy rule-based approach
to construct an aggregation matrix that allow us to
generate enhanced images for each individual observer.
As an example, we apply this approach to increase the
quality of portal images that are used in radiation
therapy.