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Importance-Aware Composition for Illustrative Volume Rendering

Non-photorealistic volume rendering, often referred as volume illustration, augments typical visualization methods to selectively emphasize or de-emphasize structures within a volumetric dataset. Illustrative visualization techniques may affect not only the rendering style of specific portions of the dataset but also their visibility, ensuring that less important regions do not occlude more important ones. Cutaway views completely remove occluding, unimportant structures - possibly also removing valuable context information - while current solutions for smooth reduction of occlusion based on importance lack precise visibility control, simplicity and generality. We introduce a new front-to-back sample composition equation for direct volume rendering that directly takes into account a measure of sample importance. The proposed method allows smooth and precise importance-based visibility control in single-pass volume rendering, assuring visibility of important structures. We provide a mathematical justification of our composition equation and demonstrate its generality by presenting several illustrative effects, which were obtained by using our composition method and a set of importance measures calculated on the fly.