Technological advances over the past decade have enabled scientists to create ever larger and more complex scientific data sets. The main challenge in Scientific Visualization is mapping high-dimensional data onto a 2D display with only 3 perceptual dimensions (RGB colors). In order to improve perception many visualization techniques utilize glyphs which encode data parameters using geometric properties such as glyph shape, size, and orientation. While glyphs have been shown to be effective in

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... wide variety of applications, they usually only show information at a single point and it is difficult to visualize multiple data fields at once in order to discover relationships between them. More perceptual dimensions can be encoded by textures, which are perceptually characterized by their spatial frequency, contrast and orientation. Recognition of patterns is accomplished using primitive textural features (textons), such as length, width and orientation, with line segment orientation being particularly important for visual segmentation of surface textures. The perceptual dimension of a texture is therefore in the ideal case the sum of the perceptual dimensions of the inherent (independent) basic attributes. Additional perceptual dimensions are given by the color distribution and spatial frequency of a texture. In this research we propose and evaluate methods for creating and combining textures for multi-field visualization. We have identified four classes of post-processing techniques for combining textural representations of field data: blending, overlay, bump mapping, and masking. We evaluated the effectiveness of these methods by using them for visualizing multiple vector fields using Line Integral Convolution (LIC) textures. Our user study suggests that blending is the most effective technique to combine multiple vector field visualization textures, while masking performs worst. There is some evidence that visualizations with smooth color changes are perceived as visually more attractive, and that aesthetics increases the perceived effectiveness of a visualization technique. Based on these results we have created a new generative formal grammar called texture grammar that combines implementations of existing visualization techniques and image compositing techniques to automatically produce visualizations, depending on the input fields. Introduction: Aim 1: Analysis of the use of textures for scientific visualization Results: Characterization of visualization techniques by visual attributes employed, spatial density, information content, and generating function Aim 2: Find perceptually motivated ways to combine textures Results: Alpha blending is frequently used in computer graphics to simulate transparencies or Report Documentation Page Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.