Fabric-Like Visualization of Tensor Field Data on Arbitrary Surfaces in Image Space

TitleFabric-Like Visualization of Tensor Field Data on Arbitrary Surfaces in Image Space
Publication TypeBook Chapter
Year of Publication2012
AuthorsEichelbaum, Sebastian, Mario Hlawitschka, Hamann Bernd, and Gerik Scheuermann
EditorLaidlaw, David H., and Vilanova Anna
Book TitleNew Developments in the Visualization and Processing of Tensor Fields
Series TitleMathematics and Visualization
PublisherSpringer Berlin Heidelberg
ISBN Number978-3-642-27342-1
AbstractTensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. It already has been shown that, by employing the metaphor of a fabric structure, tensor data can be visualized precisely on surfaces where the two eigendirections in the plane are illustrated as thread-like structures. This leads to a continuous visualization of most salient features of the tensor data set. We introduce a novel approach to compute such a visualization from tensor field data that is motivated by image-space line integral convolution (LIC). Although our approach can be applied to arbitrary, non-selfintersecting surfaces, the main focus lies on special surfaces following important features, such as surfaces aligned to the neural pathways in the human brain. By adding a postprocessing step, we are able to enhance the visual quality of the of the results, which improves perception of the major patterns.