Disambiguating Approaches to Volume Visualization
Date Issued
2015
Date
2015
Author(s)
Su, Yan-Jen
Abstract
Volume visualization is a widely used technique for scientific computing and medical imaging. According to the different types of input data, several methods were developed for visualization, such as volume rendering for scalar fields and flow visualization for vector fields. In this thesis, we develop three approaches to improve the rendering results of volume rendering and then provide a method to transform vector data into scalar data so that our methods can be applied to flow visualization. There are three critical issues in volume rendering: classification, lighting, and 3D to 2D projection of transparent structures. Without proper classification to show interesting features, it is impossible to correctly interpret the volume data. Without lighting properly, users cannot gain sufficient spatial perception. In addition, volume rendering projects multiple transparent structures into an image plane and blends them together, so ambiguities are caused by these factors. Therefore, based on the classification, lighting and perception approaches, we propose novel methods to resolve the ambiguities. With classification, only voxels’ location and intensity are combined and reduced in dimensionality to form a 2D feature space. Augmented with intensity, the new 3D space can generate a better clustering for original data such that different materials can be easily classified. For lighting, a new lighting model is proposed to interactively approximate the effect of multiple lights. This model can be easily extended to plane cutting and maximum intensity projection to allow users to view the interior of the volume better. With perception, a thaumatrope approach is implemented on a stereoscopic display to enhance spatial perception of transparent volume data and a user study was performed to verify the effectiveness. Moreover, these methods are utilized in the field of flow visualization for solving the generally faced occlusion problem in a 3D vector field. In contrast to the traditional methods based on streamline tracking, we static the transitions of all voxles and then transform the vector field to a scalar field using a Markov chain. The experiments show that the clustered result makes a brief description of the original vector field and can co-operate with our volume rendering methods for disambiguation.
Subjects
volume visualization
volume rendering
flow visualization
Type
thesis
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