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CHAPTER 1. INTRODUCTION
the book is such that it makes it much easier than before to adopt significantly
different teaching strategies, depending on course objectives and student back-
ground. F or example, it is possible with the new organization to offer a course
that emphasizes spatial techniques and covers little or no transform material.
This is not something we recommend, but it is an option that often is attractive
in programs that place little emphasis on the signal processing aspects of the
field and prefer to focus more on the implementation of spatial techniques.
1.2 One Semester Senior Course
A basic strategy in teaching a senior course is to focus on aspects of image pro-
cessing in which both the inputs and outputs of those processes are images.
In the scope of a senior course, this usually means the material contained in
Chapters 1 through 6. Depending on instructor preferences, wavelets (Chap-
ter 7) u sually are beyond the scope of coverage in a typical senior curriculum.
However, we recommend covering at least some material on image compres-
sion (Chapter 8) as outlined below.
We have found in more than three decades of teaching this material t o se-
niors in electrical engineering, computer science, and other technical disciplines,
that one of the keys to success is to spend at least one lecture on motivation
and the equivalent of one lecture on review of background material, as the need
arises . The motivational material is provided in the numerous application areas
dis1.2 One Semester Senior Coursecussed in Chapter 1. This chapter was pre-
pared with this objective in mind. Some of this material can be covered in class
in the fir st period and the rest assigned as independent reading. Background re-
view should cover probability theory (of one random variable) before histogram
processing (Section 3.3). A brief review of vectors and matrices may be required
later, depending on the material covered. The review material in the book web
site was designed f or just this purpose.
Chapter 2 should be covered in its entirety. Some of the material (Sections
2.1 through 2.3.3) can be assigned as independent r eading, but more detailed
explanation (combined with some additional independent reading) of Sections
2.3.4 and 2.4 through 2.6 is time well spent. The material in Section 2.6 covers
concepts that are used throughout the book and provides a number of image
processing applications that are useful as motivational background for the rest
of the book
Chapter 3 covers spatial intensity transformations and spatial correlation and
convolution as the foundation of spatial filtering. The chapter also covers a
number of different uses of spatial transformations and spatial filtering for im-
age enhancement. These techniques are illustrated in the context enhancement
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