***Revised***

University of Houston
Department of Computer Science

In partial fulfillment of the Requirements for the Degree of
Master of Science


Kristoffer Andersson
will defend his thesis

Interpolation of Volumetric Data for Volume Visualization



Abstract

Volume visualization is a technique where three-dimensional (volumetric) data are projected onto a two-dimensional image. While the information about the depth is lost during the projection process, addition of shading in the image is necessary to provide clues to the projected three-dimensional structures, their orientation, and relative position. In the visualization process, also called volume rendering, values between the known samples often need to be estimated using interpolation. For the inclusion of shading in the image, the derivative at any position must also be obtained.

The quality of the volume rendering result depends both on the accuracy of the interpolation, and the derivative estimation. Various interpolation and derivative estimation filters are evaluated in this thesis. The evaluation is divided into an analytical part and an experimental part. The analytical examination includes the comparison of the order of decay of the global error, the local spatial error, and the behavior of the interpolation and derivative functions in the frequency domain. In the experimental evaluation, volume visualizations of both synthetic and medical data are constructed. For the synthetic data, the interpolation and derivative estimation errors are computed and visualized as well.

Date: Tuesday, July 30, 2002
Time: 12:30 PM
Place: 218D-PGH

Faculty, students, and the general public are invited.
Thesis Advisor: Dr. Ioannis A. Kakadiaris