Quantitative effectiveness measures for direct volume rendered images

With the rapid development in graphics hardware and volume rendering techniques, many volumetric datasets can now be rendered in real time on a standard PC equipped with a commodity graphics board. However, the effectiveness of the results, especially direct volume rendered images, is difficult to validate and users may not be aware of ambiguous or even misleading information in the results. This limits the applications of volume visualization. In this paper, we introduce four quantitative effectiveness measures: distinguishability, contour clarity, edge consistency, and depth coherence measures, which target different effectiveness issues for direct volume rendered images. Based on the measures, we develop a visualization system with automatic effectiveness assessment, providing users with instant feedback on the effectiveness of the results. The case study and user evaluation have demonstrated the high potential of our system.