Image Processing Reference
In-Depth Information
7
VISUALIZATION OF 3D GRAY-TONE
IMAGES
In this chapter we discuss the visualization of a 3D gray-tone image. Explained
are tools for visualizing a 3D gray-tone image such as projection, surface
rendering, and volume rendering. These topics belong to the field of computer
graphics, and are discussed in detail in ordinary computer graphics textbooks.
Here we will discuss only the topics that are used for the visualization of a
3D gray-tone image.
7.1 Formulation of visualization problem
Let us summarize briefly the meaning of visualization as presented in this
chapter. The human eye is incapable of seeing a whole 3D gray-tone image
f ( x, y, z ). The reason is that in an image f ( x, y, z ) a density value is assigned
to every point ( x, y, z ) in 3D space, and we are unable to understand the
whole 3D space from only looking at an object in the real world with our
ordinary human vision. In order to solve this problem various methods have
been developed by using computer graphics (CG) technologies. This problem
also exists in data visualization and the development of methods for this. In
this chapter we introduce the basics of displaying or visualizing a gray-tone
3D image.
Visualization means the presentation of the whole of a 3D image in such
a way that a human observer can understand it when he or she looks at
it. Therefore, the result (the output of the visualization process) should be
drawn (or displayed) onto a 2D plane. In other words, visualization is a way
of mapping, that is, to map the distribution of density values and forms of
objects in a 3D (or higher dimensional) space onto a 2D plane. Therefore, it
is unavoidable that part of the information contained in an original 3D image
is lost except for in very specific cases. Intuitively the information concerning
the depth (the information in the direction perpendicular to an image plane)
will be lost, although some very complicated methods of compensation may be
effective in few cases. In spite of this serious information loss problem, we have
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