Image Processing Reference
In-Depth Information
Chapter 11
Categorization
Helwig Hauser and Hamish Carr
Abstract Multifield visualization covers a range of data types that can be visualized
with many different techniques. We summarize both the data types and the categories
of techniques, and lay out the reasoning for dividing this Part into chapters by tech-
nique rather than by data type.
As we have seen in the previous chapter, multifield visualization covers a broad range
of types of data. It is therefore possible to discuss multifield visualization according
to these data types, with each type covered in a separate chapter. However, it is
also possible to approach the question by considering the techniques to be applied,
many of which can be applied to multiple types of multifield data. In this chapter, we
therefore discuss bothways of analysingmultifield visualization techniques, andwhy
we have chosen to proceed according to technique rather than type in the subsequent
chapters.
11.1 Categorization by Data Type
All multifield data shares a common attribute—that it is known or presumed that the
fields are related spatially to each other. However, these relationships can arise in
different ways, and this has an impact on how we analyze or visualize the data.
Broadly speaking, the individual fields inmultifield data can be related in a number
of ways:
1. Multi-variate data, where related properties are computed or measured,
2. Spectral data, where multiple properties are measured, but may or may not be
related,
( B )
University of Bergen, Bergen, Norway
e-mail: Helwig.Hauser@UiB.no
H. Carr
University of Leeds, Leeds, UK
e-mail: H.Carr@Leeds.ac.uk
H. Hauser
 
Search WWH ::




Custom Search