Visualization

Proposes a technique for topology-preserving smoothing of sampled vector fields. The vector field data is first converted into a scalar representation in which time surfaces implicitly exist as level sets. We then locally analyze the dynamic behavior of the level sets by placing geometric primitives in the scalar field and by subsequently distorting these primitives with respect to local variations in this field. From the distorted primitives, we calculate the curvature normal and we use the normal magnitude and its direction to separate distinct flow features. Geometrical and topological considerations are then combined to successively smooth dense flow fields, at the same time retaining their topological structure.

Keywords: vector field methods, ip image processing signal processing, surface processing, ncrr

The Department of Energy and the National Science Foundation sponsored a series of workshops on data manipulation and visualization of large-scale scientific datasets. Three workshops were held in 1998, bringing together experts in high-performance computing, scientific visualization, emerging computer technologies, physics, chemistry, materials science, and engineering. These workshops were followed by two writing and review sessions, as well as numerous electronic collaborations, to synthesize the results. The results of these efforts are reported here. Across the government, mission agencies are charged with understanding scientific and engineering problems of unprecedented complexity. The DOE Accelerated Strategic Computing Initiative, for example, will soon be faced with the problem of understanding the enormous datasets created by teraops simulations, while NASA already has a severe problem in coping with the flood of data captured by earth observation satellites. Unfortunately, scientific visualization algorithms, and high-performance display hardware and software on which they depend, have not kept pace with the sheer size of emerging datasets, which threaten to overwhelm our ability to conduct research. Our capability to manipulate and explore large datasets is growing only slowly, while human cognitive and visual perception are an absolutely fixed resource. Thus, there is a pressing need for new methods of handling truly massive datasets, of exploring and visualizing them, and of communicating them over geographic distances. This report, written by representatives from academia, industry, national laboratories, and the government, is intended as a first step toward the timely creation of a comprehensive federal program in data manipulation and scientific visualization. There is, at this time, an exciting confluence of ideas on data handling, compression, telepresence, and scientific visualization. The combination of these new ideas, which we refer to as Da ta and Visualization Corridors (DVC), can raise scientific data understanding to new levels and will improve the way science is practiced