Universität Stuttgart
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Item Open Access Multi-field visualization on graphics processing units(2008) Botchen, Ralf Peter; Ertl, Thomas (Prof. Dr.)The generation of multi-field data has become commonplace in many scientific disciplines and application areas today. While researchers have produced numerous techniques for analyzing a single scalar, vector, or tensor field over the last years, finding approaches for exploring multi-field datasets still forms one of the significant challenges in visualization and analytics. One crucial aspect for the growing demand of multi-field visualization techniques is the fact that scientists need to explore the interaction of these fields to gain deeper understanding of underlying processes and relationships. This work addresses the challenge of illustrating multi-field data and presents new approaches of visualization techniques for a variety of application areas, with the aim to map these algorithms to graphics hardware architectures to achieve interactive visualization. In particular, the main contributions of this thesis contain multi-field flow visualization with one focus on integrating an additional flow uncertainty value, based on measurement simulation, into visualization. Therefore, texture based advection techniques are extended for the transport and display of the additional information. The second focus lies on the illustration of multiple fields as one combined characteristic set to minimize memory usage and allow further feature extraction from the new unique representation. New techniques are developed for multi-field volume rendering in the area of medical applications, with the primary challenge to intermix volumetric data that was acquired by different medical imaging modalities. The proposed solutions give implementation details for raycasting and slice-based rendering of multiple overlapping volumes. The third application area is video visualization. This domain is a typical representative for multi-field visualization, as it combines both, flow fields and multi-volume data for illustration. The goal of the introduced video visualization techniques is to extract dynamic or still objects in a scene, detect their individual actions and the relations among each other and to display this filtered information as a continuous stream of signatures for analysis. Another problematic issue in multi-field visualization is the size of the data, which is usually rather large. Yet, data transfer to and memory size on GPUs are two major bottlenecks. To address this issue, throughout the thesis techniques for data reduction by combination and data bricking for continuous streaming are discussed. Finally, multi-field data encoding and visualization techniques are presented that utilize the advantages of radial basis functions to minimize the data size.