Volume Visualization Techniques
Introducing Volume Visualization
Volume visualization is the creation of graphical representations of data sets that are defined on three-dimensional grids. Volume data sets are characterized by multidimensional arrays of scalar or vector data. These data are typically defined on lattice structures representing values sampled in 3-D space. Scalar data contains single values for each point. Vector data contains three values for each point, defining the components of a vector.
Examples of Volume Data
An example of scalar volume data is that produced by the flow M-file. The flow data represents the speed profile of a submerged jet within an infinite tank. Typing
[x,y,z,v] = flow;
produces four 3-D arrays. The x, y, and z arrays specify the coordinates of the scalar values in the array v.
The wind data set is an example of vector volume data that represents air currents over North America. You can load this data in to the MATLAB workspace with the command
load wind
This data set comprises six 3-D arrays - x, y, and z are the coordinate data for the arrays u, v, and w, which are the vector components for each point in the volume.
Selecting Visualization Techniques
The techniques you select to visualize volume data depend on what type of data you have and what you want to learn. In general, scalar data is best viewed with isosurfaces, slice planes, and contour slices. Vector data represents both a magnitude and direction at each point, which is best displayed by stream lines, cone plots and arrow plots. Most visualizations, however, employ a combination of techniques to best reveal the content of the data.
The sections in this topic area describe how to apply a variety of techniques to typical volume data.
Steps to Create a Volume Visualization
Creating an effective visualization requires a number of steps to compose the final scene. These steps fall into four basic categories:
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