Image Enhancement Based on Fuzzy Aggregation techniques

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.