| The amount of data available from simulation and measurement is growing at an incredible rate. A major challenge for the visualization community is to develop methods that allow users to explore these data interactively. For three-dimensional scalar fields, direct volume rendering has become an important technique in research and commercial settings. Interactive volume rendering requires the efficient use of available computational resources to keep pace with the disparity, resolution, and complexity of the volumes that are commonly produced from simulations (e.g., computational fluid dynamics or structural mechanics) and measurements (e.g., environmental observation and forecasting systems). For structured grids, direct volume rendering is well-studied and sufficiently straightforward with modern graphics hardware. This is not the case with unstructured volumes, because the elements that compose the mesh do not so easily map to current hardware. These datasets may be extremely large and contain more than a single static instance. Therefore, advanced solutions are required to achieve interactive visualization of this type of data.; The goal of this dissertation is to provide several new techniques to facilitate the visualization of disparate unstructured meshes. Two new methods are proposed to accelerate volume rendering for the case of static data, one of which operates in object-space and the other in image-space. Acceleration methods may not always be enough, however, to allow interactive visualization for data that are too large to fit in the main memory of a computer. Therefore, a new progressive rendering approach is proposed that adaptively refines a visualization using remote resources. These new techniques are of great assistance for a large class of static imagery. However, dynamic volumes that change over time create unique challenges because of the amount of data that needs to be transmitted at each step. To address this issue, a new method for efficiently handling time-varying unstructured volumes is also presented in this dissertation.; Together, these methods for interactive visualization provide a powerful framework for analyzing large amounts of unstructured data. To demonstrate this, a final application for transfer function design that combines many of these approaches is presented. This application includes an evaluation performed by a group of expert users to elaborate on the importance of these proposed techniques for interactive visualization. |
