383 research outputs found
Wavelet representation of contour sets
Journal ArticleWe present a new wavelet compression and multiresolution modeling approach for sets of contours (level sets). In contrast to previous wavelet schemes, our algorithm creates a parametrization of a scalar field induced by its contours and compactly stores this parametrization rather than function values sampled on a regular grid. Our representation is based on hierarchical polygon meshes with subdivision connectivity whose vertices are transformed into wavelet coefficients. From this sparse set of coefficients, every set of contours can be efficiently reconstructed at multiple levels of resolution. When applying lossy compression, introducing high quantization errors, our method preserves contour topology, in contrast to compression methods applied to the corresponding field function. We provide numerical results for scalar fields defined on planar domains. Our approach generalizes to volumetric domains, time-varying contours, and level sets of vector fields
09251 Abstracts Collection -- Scientific Visualization
From 06-14-2009 to 06-19-2009, the Dagstuhl Seminar 09251 ``Scientific Visualization \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, over 50 international participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general
Visualization, Exploration and Data Analysis of Complex Astrophysical Data
In this paper we show how advanced visualization tools can help the
researcher in investigating and extracting information from data. The focus is
on VisIVO, a novel open source graphics application, which blends high
performance multidimensional visualization techniques and up-to-date
technologies to cooperate with other applications and to access remote,
distributed data archives. VisIVO supports the standards defined by the
International Virtual Observatory Alliance in order to make it interoperable
with VO data repositories. The paper describes the basic technical details and
features of the software and it dedicates a large section to show how VisIVO
can be used in several scientific cases.Comment: 32 pages, 15 figures, accepted by PAS
An Isosurface Continuity Algorithm for Super Adaptive Resolution Data
We present the chain-gang algorithm for isosurface rendering of super adaptive resolution (SAR) volume data in order to minimize (1) the space needed for storage of both the data and the isosurface and (2) the time taken for computation. The chain-gan
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Volume MLS Ray Casting
The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-understood theoretical foundations. This paper applies MLS to volume rendering, providing a unified mathematical framework for ray casting of scalar data stored over regular as well as irregular grids. We use the MLS reconstruction to render smooth isosurfaces and to compute accurate derivatives for high-quality shading effects. We also present a novel, adaptive preintegration scheme to improve the efficiency of the ray casting algorithm by reducing the overall number of function evaluations, and an efficient implementation of our framework exploiting modern graphics hardware. The resulting system enables high-quality volume integration and shaded isosurface rendering for regular and irregular volume data.Engineering and Applied Science
AMM: Adaptive Multilinear Meshes
We present Adaptive Multilinear Meshes (AMM), a new framework that
significantly reduces the memory footprint compared to existing data
structures. AMM uses a hierarchy of cuboidal cells to create continuous,
piecewise multilinear representation of uniformly sampled data. Furthermore,
AMM can selectively relax or enforce constraints on conformity, continuity, and
coverage, creating a highly adaptive and flexible representation to support a
wide range of use cases. AMM supports incremental updates in both spatial
resolution and numerical precision establishing the first practical data
structure that can seamlessly explore the tradeoff between resolution and
precision. We use tensor products of linear B-spline wavelets to create an
adaptive representation and illustrate the advantages of our framework. AMM
provides a simple interface for evaluating the function defined on the adaptive
mesh, efficiently traversing the mesh, and manipulating the mesh, including
incremental, partial updates. Our framework is easy to adopt for standard
visualization and analysis tasks. As an example, we provide a VTK interface,
through efficient on-demand conversion, which can be used directly by
corresponding tools, such as VisIt, disseminating the advantages of faster
processing and a smaller memory footprint to a wider audience. We demonstrate
the advantages of our approach for simplifying scalar-valued data for commonly
used visualization and analysis tasks using incremental construction, according
to mixed resolution and precision data streams
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Hierarchical Large-scale Volume Representation with 3rd-root-of-2 Subdivision and Trivariate B-spline Wavelets
Multiresolution methods provide a means for representing data at multiple levels of detail. They are typically based on a hierarchical data organization scheme and update rules needed for data value computation. We use a data organization that is based on what we call subdivision. The main advantage of subdivision, compared to quadtree (n=2) or octree (n=3) organizations, is that the number of vertices is only doubled in each subdivision step instead of multiplied by a factor of four or eight, respectively. To update data values we use n-variate B-spline wavelets, which yield better approximations for each level of detail. We develop a lifting scheme for n=2 and n=3 based on the -subdivision scheme. We obtain narrow masks that provide a basis for out-of-core techniques as well as view-dependent visualization and adaptive, localized refinement
Variational Level-Set Detection of Local Isosurfaces from Unstructured Point-based Volume Data
A standard approach for visualizing scalar volume data is the extraction of isosurfaces. The most efficient methods for surface extraction operate on regular grids. When data is given on unstructured point-based samples, regularization can be applied but may introduce interpolation errors. We propose a method for smooth isosurface visualization that operates directly on unstructured point-based volume data avoiding any resampling. We derive a variational formulation for smooth local isosurface extraction using an implicit surface representation in form of a level-set approach, deploying Moving Least Squares (MLS) approximation, and operating on a kd-tree. The locality of our approach has two aspects: first, our algorithm extracts only those components of the isosurface, which intersect a subdomain of interest; second, the action of the main term in the governing equation is concentrated near the current isosurface position. Both aspects reduce the computation times per level-set iteration. As for most level-set methods a reinitialization
procedure is needed, but we also consider a modified algorithm where this step is eliminated. The final isosurface is extracted in form of a point cloud representation. We present a novel point completion
scheme that allows us to handle highly adaptive point sample distributions. Subsequently, splat-based or mere (shaded) point rendering is applied. We apply our method to several synthetic and real-world data sets to demonstrate its validity and efficiency
Multiple dataset visualization (MDV) framework for scalar volume data
Many applications require comparative analysis of multiple datasets representing different samples, conditions, time instants, or views in order to develop a better understanding of the scientific problem/system under consideration. One effective approach for such analysis is visualization of the data. In this PhD thesis, we propose an innovative multiple dataset visualization (MDV) approach in which two or more datasets of a given type are rendered concurrently in the same visualization. MDV is an important concept for the cases where it is not possible to make an inference based on one dataset, and comparisons between many datasets are required to reveal cross-correlations among them. The proposed MDV framework, which deals with some fundamental issues that arise when several datasets are visualized together, follows a multithreaded architecture consisting of three core components, data preparation/loading, visualization and rendering. The visualization module - the major focus of this study, currently deals with isosurface extraction and texture-based rendering techniques. For isosurface extraction, our all-in-memory approach keeps datasets under consideration and the corresponding geometric data in the memory. Alternatively, the only-polygons- or points-in-memory only keeps the geometric data in memory. To address the issues related to storage and computation, we develop adaptive data coherency and multiresolution schemes. The inter-dataset coherency scheme exploits the similarities among datasets to approximate the portions of isosurfaces of datasets using the isosurface of one or more reference datasets whereas the intra/inter-dataset multiresolution scheme processes the selected portions of each data volume at varying levels of resolution. The graphics hardware-accelerated approaches adopted for MDV include volume clipping, isosurface extraction and volume rendering, which use 3D textures and advanced per fragment operations. With appropriate user-defined threshold criteria, we find that various MDV techniques maintain a linear time-N relationship, improve the geometry generation and rendering time, and increase the maximum N that can be handled (N: number of datasets). Finally, we justify the effectiveness and usefulness of the proposed MDV by visualizing 3D scalar data (representing electron density distributions in magnesium oxide and magnesium silicate) from parallel quantum mechanical simulation
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