Derived Fields - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 130

Chapter 14
Derived Fields

Eugene Zhang and Vijay Natarajan

Abstract This chapter reviews various methods for multifield visualization that
are based on the notion of derived fields. The derived fields are categorized based
on properties like the number and type of input fields. Mathematical properties,
algorithms, and applications are discussed for each derived field. Correlation and
alignment measures are examined for a set of homogeneous fields, including pairwise
similarity/dissimilarity measurements. Multifield analysis is also discussed in the
context of input fields being the components of the decomposition of another field,
possibly of a different type. Finally, research challenges are discussed in the context
of the design of multifield analysis and visualization methods based on the concept
of derived fields.

14.1 Introduction

In this chapter we consider the notion of derived fields in the context of multifield
analysis and visualization. We discuss a categorization based on the number of fields
studied, their homogeneity, and the type of relationship between the input fields that
is captured by the derived field.
First, given a set of at least two fields of the same type, it is possible to define
pairwise similarity and dissimilarity for any two of the fields as well as the global
alignment and dependency of the fields considered as a whole. These quantities,

( B )
School of Electrical Engineering and Computer Science,2111 Kelley Engineering Center,
Oregon State University, Corvallis, OR 97331, USA
e-mail: [e-mail]
V. Natarajan
Department of Computer Science and Automation, Supercomputer Education and Research
Center, Indian Institute of Science, Bangalore 560012, India
e-mail: [e-mail]

E. Zhang