Summary: Chapter 4
MIT Media Laboratory Vision and Modeling Technical Report #137.
Appears in: "Subband Coding", edited by John Woods, Kluwer Academic Press, 1990.
Eero P. Simoncelliy and Edward H. Adelsonz
Vision Science Group, The Media Laboratory, and
yDepartment of Electrical Engineering and Computer Science
zDepartment of Brain and Cognitive Science
Massachusetts Institute of Technology
Cambridge, Massachusetts 02139
Linear transforms are the basis for many techniques used in image pro-
cessing, image analysis, and image coding. Subband transforms are a subclass
of linear transforms which oer useful properties for these applications. In
this chapter, we discuss a variety of subband decompositions and illustrate
their use in image coding. Traditionally, coders based on linear transforms
are divided into two categories: transform coders and subband coders. This
distinction is due in part to the nature of the computational methods used for
the two types of representation.
Transform coding techniques are usually based on orthogonal linear trans-
forms. The classic example of such a transform is the discrete Fourier trans-