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In the literature on optimal regular volume sampling, the Body-Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band-limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face-Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well-known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner-Lobb test signal such that an undue advantage is not given to either lattice. [ABSTRACT FROM AUTHOR]

This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided. [ABSTRACT FROM AUTHOR]

We present a visualization tool for the real-time analysis of interactively steered ensemble-simulation runs, and apply it to flooding simulations. Simulations are performed on-the-fly, generating large quantities of data. The user wants to make sense of the data as it is created. The tool facilitates understanding of what happens in all scenarios, where important events occur, and how simulation runs are related. We combine different approaches to achieve this goal. To maintain an overview, data are aggregated and embedded into the simulation rendering, showing trends, outliers, and robustness. For a detailed view, we use information-visualization views and interactive visual analysis techniques. A selection mechanism connects the two approaches. Points of interest are selected by clicking on aggregates, supplying data for visual analysis. This allows the user to maintain an overview of the ensemble and perform analysis even as new data are supplied through simulation steering. Unexpected or unwanted developments are detected easily, and the user can focus the exploration on them. The solution was evaluated with two case studies focusing on placing and testing flood defense measures. Both were evaluated by a consortium of flood simulation and defense experts, who found the system to be both intuitive and relevant. [ABSTRACT FROM AUTHOR]

In this paper, we describe a novel approach for applying texture mapping to volumetric data sets. In contrast to previous approaches, the presented technique enables a unified integration of 2D and 3D textures and thus allows to emphasize material boundaries as well as volumetric regions within a volumetric data set at the same time. One key contribution of this paper is a parametrization technique for volumetric data sets, which takes into account material boundaries and volumetric regions. Using this technique, the resulting parametrizations of volumetric data sets enable texturing effects which create a higher degree of realism in volume rendered images. We evaluate the quality of the parametrization and demonstrate the usefulness of the proposed concepts by combining volumetric texturing with volumetric lighting models to generate photorealistic volume renderings. Furthermore, we show the applicability in the area of illustrative visualization. [ABSTRACT FROM AUTHOR]

Displaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2×2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

We introduce a novel method for identification of objects of interest in volume data. Our approach conveys the information contained in two essentially different concepts, the object''s boundaries and the narrow solid structures, in an easy and uniform way. The second-order derivative operators in directions reaching minimal response are employed for this task. To show the superior performance of our method, we provide a comparison with its main competitor—surface extraction from areas of maximal gradient magnitude. We show that our approach provides the possibility to represent volume data by a subset of a nominal size. Practical applications of our method include fast volume display due to object-space oriented techniques, progressive visualization over the network and the related generation of preview data sets for web-based repositories. For these applications, the size of the representative subset can be estimated automatically with respect to the bottleneck of the visualization system or network bandwidth. [Copyright &y& Elsevier]

The article discusses various reports published within the issue, including one by Jarke J. van Wijk on visualization and another by Ofri Sadowsky and colleagues on barycentric formulation applied to digital radiograph reconstruction using higher-order attenuation.

In visualization systems it is often the case that the changes of the input parameters are not proportional to the visual change of the generated output. In this paper, we propose a model for enabling data-sensitive navigation for user-interface elements. This model is applied to normalize the user input according to the visual change, and also to visually communicate this normalization. In this way, the exploration of heterogeneous data using common interaction elements can be performed in an efficient way. We apply our model to the field of medical visualization and present guided navigation tools for traversing vascular structures and for camera rotation around 3D volumes. The presented examples demonstrate that the model scales to user-interface elements where multiple parameters are set simultaneously. [ABSTRACT FROM AUTHOR]

We investigate uncertainty guidance mechanisms to support proton therapy (PT) planning visualization. Uncertainties in the PT workflow pose significant challenges for navigating treatment plan data and selecting the most optimal plan among alternatives. Although guidance techniques have not yet been applied to PT planning scenarios, they have successfully supported sense- and decision-making processes in other contexts. We hypothesize that augmenting PT uncertainty visualization with guidance may influence the intended users' perceived confidence and provide new insights. To this end, we follow an iterative co-design process with domain experts to develop a visualization dashboard enhanced with distinct level-of-detail uncertainty guidance mechanisms. Our approach classifies uncertainty guidance into two dimensions: degree of intrusiveness and detail-orientation. Our dashboard supports the comparison of multiple treatment plans (i.e., nominal plans with their translational variations) while accounting for multiple uncertainty factors. We subsequently evaluate the designed and developed strategies by assessing perceived confidence and effectiveness during a sense- and decision-making process. Our findings indicate that uncertainty guidance in PT planning visualization does not necessarily impact the perceived confidence of the users in the process. Nonetheless, it provides new insights and raises uncertainty awareness during treatment plan selection. This observation was particularly evident for users with longer experience in PT planning. [Display omitted] • A dashboard for tumor PT plan comparison to tackle multiple sources of uncertainty. • Multi-level-of-detail guidance mechanisms to facilitate navigation of uncertainties. • An evaluation approach to validate uncertainty guidance in PT visualization. [ABSTRACT FROM AUTHOR]

In this paper we present a fast visualization technique for volumetric data, which is based on a recent non-photorealistic rendering technique. Our new approach enables alternative insights into 3D data sets (compared to traditional approaches such as direct volume rendering or iso-surface rendering). Object contours, which usually are characterized by locally high gradient values, are visualized regardless of their density values. Cumbersome tuning of transfer functions, as usually needed for setting up DVR views is avoided. Instead, a small number of parameters is available to adjust the non-photorealistic display. Based on the magnitude of local gradient information as well as on the angle between viewing direction and gradient vector, data values are mapped to visual properties (color, opacity), which then are combined to form the rendered image (MIP is proposed as the default compositing stragtegy here). Due to the fast implementation of this alternative rendering approach, it is possible to interactively investigate the 3D data, and quickly learn about internal structures. Several further extensions of our new approach, such as level lines are also presented in this paper. [ABSTRACT FROM AUTHOR]

• Visualization research relies on software development • Reward discrepancy exists between novel research and necessary software development • Visualization software is hard to design, assess, compare, use and maintain • Considerations on prototypes and extension/development of frameworks • We give advice about, identify provisions for and discuss software in our community. Visualization has evolved into a mature scientific field and it has also become widely accepted as a standard approach in diverse fields, including physics, life sciences, and business intelligence. However, despite its successful development, there are still many open research questions that require customized implementations in order to explore and establish concepts, and to perform experiments and take measurements. Many methods and tools have been developed and published but most are stand-alone prototypes and have not reached a mature state that can be used in a reliable manner by collaborating domain scientists or a wider audience. In this study, we discuss the challenges, solutions, and open research questions that affect the development of sophisticated, relevant, and novel scientific visualization solutions with minimum overheads. We summarize and discuss the results of a recent National Institute of Informatics Shonan seminar on these topics. [ABSTRACT FROM AUTHOR]

Abstract: We present an interactive graphical approach for the explicit specification of semantics for volume visualization. This explicit and graphical specification of semantics for volumetric features allows us to visually assign meaning to both input and output parameters of the visualization mapping. This is in contrast to the implicit way of specifying semantics using transfer functions. In particular, we demonstrate how to realize a dynamic specification of semantics which allows to flexibly explore a wide range of mappings. Our approach is based on three concepts. First, we use semantic shader augmentation to automatically add rule-based rendering functionality to static visualization mappings in a shader program, while preserving the visual abstraction that the initial shader encodes. With this technique we extend recent developments that define a mapping between data attributes and visual attributes with rules, which are evaluated using fuzzy logic. Second, we let users define the semantics by analogy through brushing on renderings of the data attributes of interest. Third, the rules are specified graphically in an interface that provides visual clues for potential modifications. Together, the presented methods offer a high degree of freedom in the specification and exploration of rule-based mappings and avoid the limitations of a linguistic rule formulation. [Copyright &y& Elsevier]