Direct volume rendering (DVR) is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images (DVRIs). However, some important parts of interesting structures can be missing in the DVRIs due to occlusion problems. We propose two techniques to address these problems in this thesis. First, we present VoxelBars as an informative interface for volume visualization. VoxelBars arrange voxels into a 2D space and visually encode multiple attributes of voxels into one display. With VoxelBars, users can easily find clusters of interesting voxels and set properties of a specific group of...[ Read more ]

Direct volume rendering (DVR) is a powerful visualization technique which allows users to effectively explore and study volumetric datasets. Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images (DVRIs). However, some important parts of interesting structures can be missing in the DVRIs due to occlusion problems. We propose two techniques to address these problems in this thesis. First, we present VoxelBars as an informative interface for volume visualization. VoxelBars arrange voxels into a 2D space and visually encode multiple attributes of voxels into one display. With VoxelBars, users can easily find clusters of interesting voxels and set properties of a specific group of voxels. Various sophisticated visualization tasks dealing with occlusion problems can be achieved. Second, we investigate how to semi-automatically generate a set of visibility-aware DVRIs and also an animation which can reveal information that is missing in the original DVRIs and meanwhile satisfy some image quality criteria such as context and coherence. A complete framework is developed to tackle various problems related to generation and quality evaluation of visibility-aware DVRIs and animations.