Issues on Displaying 3D Data for Scientific Visualization
Institute of Computer Graphics
Vienna University of Technology
Line Integral Convolution (LIC) is an elegant algorithm for visualizing vector fields. Very good results are achieved for 2D vector fields, but extending it to 3D arises some problems. The pictures get confusing, too many details obscure the flow topology. Some modifications to the original algorithm have been proposed by Interrante and Grosch  to achieve better results in three dimensions.
The texture used with 2D LIC would normally be an opaque, uncorrelated white noise. This has the drawback that the orientation of the vector field cannot be perceived. Wegenkittl et al.  developed a method, Oriented Line Integral Convolution (OLIC), where they use a low frequency input texture and a ramp like convolution kernel to depict both direction and orientation of the flow. This, further, inspired Interrante and Grosch to enhance 3D LIC by using a sparsely opaque input texture and to use LIC to correlate both color and opacity values in the direction of the flow. They also proposed that the input spots in the volume should be randomly situated according to an approximate Poisson-disk distribution, rather than laid out purely randomly. See Figure 3 for an example.
Figure 3: Volume Line Integral Convolution from an input texture of evenly-distributed random point samples. Shading is computed as described in Section 2.1.
If the stream lines are shaded as described in Section 2.1, the local orientation of the flow can be clearly depicted but streamlines that are separated in depth but which flow in a similar direction cannot effectively be distinguished. The following techniques have proven useful for clarifying the display of volume textures generated via 3D LIC: