3-D Visualization

Overview of 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. There are two basic types of volume data:

• Scalar volume data contains single values for each point.
• Vector volume data contains two or 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 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 (particles, ribbons, and tubes), cone plots, and arrow plots. Most visualizations, however, employ a combination of techniques to best reveal the content of the data.

The material in these sections describes 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:

1. Determine the characteristics of your data. Graphing volume data usually requires knowledge of the range of both the coordinates and the data values.
2. Select an appropriate plotting routine. The information in this section helps you select the right methods.
3. Define the view. The information conveyed by a complex three-dimensional graph can be greatly enhanced through careful composition of the scene. Viewing techniques include adjusting camera position, specifying aspect ratio and project type, zooming in or out, and so on.
4. Add lighting and specify coloring. Lighting is an effective means to enhance the visibility of surface shape and to provide a three-dimensional perspective to volume graphs. Color can convey data values, both constant and varying.

Volume Visualization Techniques

Volume Visualization Functions

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