Per-Pixel Opacity Modulation for Feature Enhancement in Volume Rendering

Classical direct volume rendering techniques accumulate color and opacity contributions using the standard volume rendering equation approximated by alpha blending. However, such standard rendering techniques, often also aiming at visual realism, are not always adequate for efficient data exploration, especially when large opaque areas are present in a data set, since such areas can occlude important features and make them invisible. On the other hand, the use of highly transparent transfer functions allows viewing all the features at once, but often makes these features barely visible. In order to enhance feature visibility, we present in this paper a straightforward rendering technique that consists of modifying the traditional volume rendering equation. Our approach does not require an opacity transfer function, and instead is based on a function quantifying the relative importance of each voxel in the final rendering called relevance function. This function is subsequently used to dynamically adjust the opacity of the contributions per pixel. We conduct experiments with a number of possible relevance functions in order to show the influence of this parameter. As will be shown by our comparative study, our rendering method is much more suitable than standard volume rendering for interactive data exploration at a low extra cost. Thereby, our method avoids feature visibility restrictions without relying on a transfer function and yet maintains a visual similarity with standard volume rendering.