New PDF release: 63.Visualization and Computer Graphics

By John G. Webster (Editor)

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INFORMATION VISUALIZATION Information visualization is the application of 2-D and 3-D visualization techniques to information, whether these data are spatial or not. With this broad definition, scientific or engineering data visualization would also fall under the information visualization mantle. More typically information visualization is understood to deal with data that has one or more nonspatial components. Thus the inventories of a chain of stores, whether or not their geographical distribution is taken into account, would be a subject for information visualization.

For a given isovalue S0 there might be multiple surfaces, some of which could be inside others. By changing the isovalue, one could get a depiction of the whole dataset. For example, if one had 3-D magnetic resonance imaging (MRI) data for a human head, one could choose an isovalue that shows the skull and then change the isovalue to show different regions in the brain. This is because the MRI intensity at each point depends on the depth and density at that point. See Fig. 1 for an example. Volume visualization or volume rendering is often used to depict 3-D scalar fields.

Adjacent nodes can be found by incrementing any of the index vector components. Many operations on this type of grid (such as searching the grid cell which contains a given point) are very simple, but grid density is constant throughout the domain, and the shape of the domain must be rectangular. The second type of grid is the structured, curvilinear grid [Fig. 1(b)]. This type has a regular topology (the adjacency pattern for each internal node is the same), with the nodes again referenced by a 3-D index vector i(i, j, k), and adjacent nodes can be found by incrementing index values.

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63.Visualization and Computer Graphics by John G. Webster (Editor)


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