Robert J. Moorhead

A User Study to Compare Four Uncertainty Visualization Methods for 1D and 2D Datasets

Many techniques have been proposed to show uncertainty in data visualizations. However, very little is known about their effectiveness in conveying meaningful information. In this paper, we present a user study that evaluates the perception of uncertainty amongst four of the most commonly used techniques for visualizing uncertainty in one-dimensional and two-dimensional data. The techniques evaluated are traditional errorbars, scaled size of glyphs, color-mapping on glyphs, and color-mapping of uncertainty on the data surface. The study uses generated data that was designed to represent the systematic and random uncertainty components. Twenty-seven users performed two types of search tasks and two types of counting tasks on 1D and 2D datasets. The search tasks involved finding data points that were least or most uncertain. The counting tasks involved counting data features or uncertainty features. A 4 times 4 full-factorial ANOVA indicated a significant interaction between the techniques used and the type of tasks assigned for both datasets indicating that differences in performance between the four techniques depended on the type of task performed. Several one-way ANOVAs were computed to explore the simple main effects. Bonferronnis correction was used to control for the family-wise error rate for alpha-inflation. Although we did not find a consistent order among the four techniques for all the tasks, there are several findings from the study that we think are useful for uncertainty visualization design. We found a significant difference in user performance between searching for locations of high and searching for locations of low uncertainty. Errorbars consistently underperformed throughout the experiment. Scaling the size of glyphs and color-mapping of the surface performed reasonably well. The efficiency of most of these techniques were highly dependent on the tasks performed. We believe that these findings can be used in future uncertainty visualization design. In addition, the framework developed in this user study presents a structured approach to evaluate uncertainty visualization techniques, as well as provides a basis for future research in uncertainty visualization.

An Advanced Evenly-Spaced Streamline Placement Algorithm

This paper presents an advanced evenly-spaced streamline placement algorithm for fast, high-quality, and robust layout of flow lines. A fourth-order Runge-Kutta integrator with adaptive step size and error control is employed for rapid accurate streamline advection. Cubic Hermite polynomial interpolation with large sample-spacing is adopted to create fewer evenly-spaced samples along each streamline to reduce the amount of distance checking. We propose two methods to enhance placement quality. Double queues are used to prioritize topological seeding and to favor long streamlines to minimize discontinuities. Adaptive distance control based on the local flow variance is explored to reduce cavities. Furthermore, we propose a universal, effective, fast, and robust loop detection strategy to address closed and spiraling streamlines. Our algorithm is an order-of-magnitude faster than Jobard and Lefers algorithm with better placement quality and over 5 times faster than Mebarki et al.s algorithm with comparable placement quality, but with a more robust solution to loop detection

Color Display for Hyperspectral Imagery

This paper investigates RGB color composition schemes for hyperspectral imagery display. A three-channel composite inevitably loses a significant amount of information contained in the original high-dimensional data. The objective here is to display the useful information as distinctively as possible for high-class separability. To achieve this objective, it is important to find an effective data processing step prior to color display. A series of supervised and unsupervised data transformation and classification algorithms are reviewed, implemented, and compared for this purpose. The resulting color displays are evaluated in terms of class separability using a statistical detector and perceptual color distance. We demonstrate that the use of the data processing step can significantly improve the quality of color display, whereas data classification generally outperforms data transformation, although the implementation is more complicated. Several instructive suggestions for practitioners are provided.

NIH-NSF visualization research challenges report summary

The US National Science Foundation (NSF) convened a panel to report on the potential of visualization as a new technology. The NSF and US National Institutes of Health (NIH) convened the Visualization Research Challenges (VRC) Executive Committee to write a new report. Here, we summarize that new VRC report. We explore the state of the field, examine the potential impact of visualization on areas of national and international importance, and present our findings and recommendations for the future of our growing discipline. Our audience is twofold: the supporters, sponsors, and application users of visualization research on the one hand, and researchers and practitioners in visualization on the other. We direct our discussion toward solving key problems of national interest and helping this works sponsors to concentrate resources to the greatest effect. Our findings and recommendations reflect information gathered from visualization and applications scientists during two workshops on VRC, as well as input from the larger visualization community.

Visualization of fluid flows in virtual environments

Visualization of Fluid Flows in Virtual Environments Ziegele , S. B. r r 1), Gopal, G. P. 1), Blades, E. 2), Moo head, R. J. 1), Marcum, D. L. 2) and Guan, Y. 1) 1) ERC GRI Visualization, Analysis and Imaging Laboratory, Mississippi State University, MS, U.S.A. E-mail : {sean | gopi | rjm | guanyl } @gri.msstate.edu 2) ERC SimCenter, Mississippi State University, MS, U.S.A., E-mail : { blades | marcum } @simcenter.msstate.edu

Wavelets applied to loseless compression and progressive transmission of floating point data in 3-D curvilinear grids

A method of lossless compression using wavelets is presented that enables progressive transmission of computational fluid dynamics (CFD) data in PLOT3D format. The floating point data is first converted to double-precision floating point format to maintain adequate precision throughout the transform process. It is then transformed using Haar wavelets-four times in two spatial dimensions, twice in the third spatial dimension, and twice in time for a total compression factor of 64 times. The double precision format will maintain enough precision during the transform to keep the process lossless. Next, the transformed data is compressed using Huffman coding and transmitted progressively using spectral selection. This allows most of the information to be transmitted in the first pass. Details are transmitted in later passes which ultimately provide for lossless reconstruction of the original data.

Progressive transmission of scientific data using biorthogonal wavelet transform

An important issue in scientific visualization systems is the management of data sets. Most data sets in scientific visualization, whether created by measurement or simulation, are usually voluminous. The goal of data management is to reduce the storage space and the access time of these data sets to speed up the visualization process. A new progressive transmission scheme using spline biorthogonal wavelet bases is proposed in this paper. By exploiting the properties of this set of wavelet bases, a fast algorithm involving only additions and subtractions is developed. Due to the multiresolutional nature of the wavelet transform, this scheme is compatible with hierarchical-structured rendering algorithms. The formula for reconstructing the functional values in a continuous volume space is given in a simple polynomial form. Lossless compression is possible, even when using floating-point numbers. This algorithm has been applied to data from a global ocean model. The lossless compression ratio is about 1.5:1. With a compression ratio of 50:1, the reconstructed data is still of good quality. Several other wavelet bases are compared with the spline biorthogonal wavelet bases. Finally the reconstructed data is visualized using various algorithms and the results are demonstrated.<<ETX>>

Hyperspectral Imagery Visualization Using Double Layers

Displaying the abundant information contained in a hyperspectral image is a challenging problem. Almost any visualization approach reduces the information content. However, we want to maximize the amount of object or material information presented. A visualization approach that uses classification as an intermediate step may maximize the information transfer. In our research, we are particularly interested in the display of mixed-pixel classification results, since most pixels in a remotely sensed hyperspectral image are mixed pixels. In this paper, we propose a visualization technique that employs two layers to integrate the mixture information (i.e., endmembers and their abundances) in each pixel. Images can be displayed with any desired level of details.

Accelerated unsteady flow line integral convolution

Unsteady flow line integral convolution (UFLIC) is a texture synthesis technique for visualizing unsteady flows with high temporal-spatial coherence. Unfortunately, UFLIC requires considerable time to generate each frame due to the huge amount of pathline integration that is computed for particle value scattering. This paper presents accelerated UFLIC (AUFLIC) for near interactive (1 frame/second) visualization with 160,000 particles per frame. AUFLIC reuses pathlines in the value scattering process to reduce computationally expensive pathline integration. A flow-driven seeding strategy is employed to distribute seeds such that only a few of them need pathline integration while most seeds are placed along the pathlines advected at earlier times by other seeds upstream and, therefore, the known pathlines can be reused for fast value scattering. To maintain a dense scattering coverage to convey high temporal-spatial coherence while keeping the expense of pathline integration low, a dynamic seeding controller is designed to decide whether to advect, copy, or reuse a pathline. At a negligible memory cost, AUFLIC is 9 times faster than UFLIC with comparable image quality

Topology-Aware Evenly Spaced Streamline Placement

This paper presents a new streamline placement algorithm that produces evenly spaced long streamlines while preserving topological features of a flow field. Singularities and separatrices are extracted to decompose the flow field into topological regions. In each region, a seeding path is selected from a set of streamlines integrated in the orthogonal flow field. The uniform sample points on this path are then used as seeds to generate streamlines in the original flow field. Additional seeds are placed where a large gap between adjacent streamlines occurs. The number of short streamlines is significantly reduced as evenly spaced long streamlines spawned along the seeding paths can fill the topological regions very well. Several metrics for evaluating streamline placement quality are discussed and applied to our method as well as some other approaches. Compared to previous work in uniform streamline placement, our method is more effective in creating evenly spaced long streamlines and preserving topological features. It has the potential to provide both intuitive perception of important flow characteristics and detail reconstruction across visually pleasing streamlines.