Direct volume rendering maps data values to visual properties such as transparency and color through transfer functions. Traditional multi-dimensional functions are generated based on a 2D histogram of function value and gradient magnitude. When two different features overlap in the 2D histogram, the traditional transfer functions cannot visually distinguish the features, since overlapped areas have similar visual properties. In this paper, we describe a new multi-dimensional transfer function that enables visual differentiation of features even in the case when two different features overlap in the 2D histogram. Furthermore, we provide details of an implementation of our transfer function on modern programmable graphics hardware.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.