Abstract
Volume visualization has been widely used to depict complicated 3D structures in volume data sets. However, obtaining clear visualization of the features of interest in a volume is still a major challenge. The clarity of features depends on the transfer function, the viewpoint and the spatial distribution of features in the volume data set. In this paper, we propose visibility-weighted saliency as a measure of visual saliency of features in volume rendered images, in order to assist users in choosing suitable viewpoints and designing effective transfer functions to visualize the features of interest. Visibility-weighted saliency is based on a computational measure of perceptual importance of voxels and the visibility of features in volume rendered images. The effectiveness of this scheme is demonstrated by test results on two volume data sets.
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