A fuzzy logic model of visual importance for efficient image synthesis

Experiments have shown that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these regions of interest contain low level feature differences that influence the fixation time of the viewer. In this paper we present a novel fuzzy logic model of visual attention which seeks to compute the relative visual importance of regions in an image based upon these spatial feature differences. We also demonstrate some of the possible savings to be had in applying the visual importance model to the modulation of super-sampling in a ray-traced image. We expect this approach to have applications in the entertainment industry where image fidelity may be sacrificed for efficiency purposes.