3D Flow Visualization Using Volume Line Integral Convolution

Introduction Line integral convolution (LIC) is a flow-driven texture generation method that has become one of the best-known and most commonly used techniques in computer graphics for visualizing 2D flow, or flow over a surface in 3D. The popularity of LIC as a tool for 3D flow visualization, or the depiction of flow through a volume, has been relatively limited in contrast, however, primarily due to the difficulties inherent in clearly and effectively portraying a dense volume texture in a static, 2D image. Over the past months, we have been investigating strategies for more effectively using 3D LIC for the visualization of 3D flow. Much of this work is described in our ICASE Report No. 97-35. In this article we highlight new results from our continuing work in this area. Background and Motivation Given a vector field and an input texture, line integral convolution produces an output texture in which the data values are highly correlated in the direction of the flow. Our work focuses on methods for effectively representing the flow information contained in the dense volumetric textures produced by 3D LIC. Our strategies include selectively emphasizing flow information in critical regions of interest in the volume and clarifying the 3D structure of the flow by facilitating the perceptual differentiation of the densely clustered streamlines. Region of Interest Definition By concentrating the 3D texture in the most significant areas of the flow, we can clarify the visual representation of the data and facilitate the appreciation of the most relevant information. When LIC is used in conjunction with a region of interest (ROI) definition based on the value of a scalar quantity across the volume, we have found that best results are achieved when the ROI mask is applied to the input texture rather than to the output. Figure 1 compares the two effects.