Intuitive transfer function editing using relative visibility histograms

Abstract

In this paper, we present an interactive approach for intuitively editing colors and opacity values in transfer functions for volume visualization. We introduce the concept of a relative visibility histogram, which represents the difference between the global visibility distribution across the full volume and the local visibility distribution within a user-selected region in the viewport. From this measure, we can infer what subset of the 3D volume the user intends to select when they click on a region in the 2D rendered image of the data set, and use this to modify relevant parts of the transfer function. We use this selection mechanism for two alternative purposes. The first is to allow output-driven editing of the transfer function, whereby a user can change the opacity values and colors of features without directly having to manipulate the transfer function itself. The second is to extract visually dominant features in any user-selected region of interest, so that the user may individually edit their appearance and then merge these to create new transfer functions. Our approach is lightweight compared to similar techniques and performs in real-time.