As part of a larger effort exploring alternative display systems, Lawrence Livermore National Laboratory has installed systems in two offices that extend and update the previously described "Office of Real Soon Now" project to improve the value for visualization tasks. These new systems use higher resolution projectors driven by workstations that run Unix-based applications via Linux and support hardware-accelerated 3D graphics, even across the boundary between displays.

The goal of this paper is to lay a foundation for objectively comparing volume-rendered images, leading to objective evaluation of their accuracy and quality. The key elements of the foundation are: (1) a rigorous specification of all the input and parameters that need to be specified to define the conditions under which a volume-rendered image is generated; and (2) the basis for a methodology for difference classification, including a suite of functions or metrics to quantify and classify the difference between two volume-rendered images that will support an analysis of the relative importance of particular differences. The results of this method can be used to study the changes caused by modifying particular parameter values, to compare and quantify changes between images of similar data sets rendered in the same way, and to detect errors in the design, implementation or modification of a volume-rendering system. If a benchmark image is available, for example one created by a high-accuracy volume-rendering system, the method can be used to evaluate the accuracy of a given image. The key contribution of this paper is the separation of the difference into noise, bias and structured difference components. Copyright © 1999 John Wiley & Sons, Ltd.

This case study describes the design and development of VISOR (Visual Integration of Simulated and Observed Results), a tool which supports the visualization and analysis of a wide variety of data relevant to aerospace engineering design. Integrating data from such disparate sources is challenging; overcoming the obstacles results in a powerful tool. The process has also been valuable in exposing requirements for the libraries of reusable software tools for visualization and data analysis being developed at NASA Ames.

The paper describes the architecture of a data level comparative visualization system and experiences using it to study computational fluid dynamics data and experimental wind tunnel data. We illustrate how the system can be used to compare data sets from different sources, data sets with different resolutions and data sets computed using different mathematical models of fluid flow. Suggested improvements to the system based on user feedback are also discussed.

Software has been developed to apply visualization techniques to aeronautics data collected during wind tunnel experiments. Interaction between the software developers and the aeroscientists has been crucial in making the software. The interaction has also been important in building the scientists' confidence in the use of interactive, computer-mediated analysis tools.

No abstract available.

In this paper we introduce B-spline illumination maps and their generalizations and extensions for use in realistic image generation algorithms. The B-spline lighting functions (i.e., illumination maps) are defined as weighted probability density functions. The lighting functions can be estimated from random data and may be used in bidirectional distributed ray tracing programs as well as radiosity oriented algorithms. The use of these lighting functions in a bidirectional ray tracing system that can handle dispersion as well as the focusing of light through lenses is presented.

A discussion is given on the validation, verification and evaluation of scientific visualization software. A "bug" usually refers to software doing something different than the programmer intended. Comprehensive testing, especially for software intended for use in innovative environments, is hard. Descriptions and summaries of the tests we have done are often not available to the users. A different source of visualization errors is software that does something different than what the scientist thinks it does. The particular methods used to compute values in the process of creating visualizations are important to the scientists, but vendors are understandably reluctant to reveal all the internals of their products. Is there a workable compromise? Another vulnerability of visualization users is in the choice of a technique which is less effective than others equally available. Visualization researchers and developers should give users the information required to make good decisions about competing visualization techniques. What information is needed? What will it take to gather and distribute it? How should it be tied to visualization software?.>

Cook, Porter, and Carpenter coined the phrase "distributed ray tracing" to describe a technique for using each ray of a super-sampled ray tracing procedure as a sample in several dimensions to achieve effects such as penumbras and motion blur in addition to spatial anti-aliasing. The shade to be displayed at a pixel is a weighted integral of the image function. The purpose of using many rays per pixel is to estimate the value of this integral. In this work, a relationship between the number of sample rays and the quality of the estimate of this integral is derived. Furthermore, the number of rays required does not depend on the dimensionality of the space being sampled, but only on the variance of the multi-dimensional image function. The algorithm has been optimized through the use of statistical testing and stratified sampling.

No abstract available.