Graduation date: 2007The Line Integral Convolution (LIC) is a mainstay of flow visualization. It is, however, computationally intensive, which limits its interactivity. Also, when used to view three-dimensional (3D) vector fields, the resulting images are dense and cluttered, making it difficult to perceive the flow on the interior parts of the field. This thesis describes research to make the 3D LIC more interactive by implementing it on the Graphics Processor Unit (GPU). It also includes methods to improve the clarity of the 3D LIC images. The volume dataset and a 3D noise volume are placed in GPU memory as 3D textures. The GPU is then used to perform the LIC computations and display the resulting volume. This allows the user to dynamically adjust LIC parameters and derive more insight into the 3D flow field. Various techniques such as introduction of sparsity and the use of stereographics help to de-clutter the scene. Resulting images and timing benchmarks are included.