23-05-2012, 10:34 AM
Digital Image Processing
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Introduction
Interest in digital image processing methods stems from two principal application
areas: improvement of pictorial information for human interpretation; and
processing of image data for storage, transmission, and representation for autonomous
machine perception.This chapter has several objectives: (1) to define
the scope of the field that we call image processing; (2) to give a historical perspective
of the origins of this field; (3) to give an idea of the state of the art in
image processing by examining some of the principal areas in which it is applied;
(4) to discuss briefly the principal approaches used in digital image processing;
(5) to give an overview of the components contained in a typical,
general-purpose image processing system; and (6) to provide direction to the
books and other literature where image processing work normally is reported.
What Is Digital Image Processing?
An image may be defined as a two-dimensional function, f(x, y), where x and
y are spatial (plane) coordinates, and the amplitude of f at any pair of coordinates
(x, y) is called the intensity or gray level of the image at that point.When
x, y, and the amplitude values of f are all finite, discrete quantities, we call the
image a digital image.The field of digital image processing refers to processing
digital images by means of a digital computer. Note that a digital image is composed
of a finite number of elements, each of which has a particular location and
Introduction
value.These elements are referred to as picture elements, image elements, pels,
and pixels. Pixel is the term most widely used to denote the elements of a digital
image.We consider these definitions in more formal terms in Chapter 2.
Vision is the most advanced of our senses, so it is not surprising that images
play the single most important role in human perception. However, unlike
humans, who are limited to the visual band of the electromagnetic (EM) spectrum,
imaging machines cover almost the entire EM spectrum, ranging from
gamma to radio waves.They can operate on images generated by sources that
humans are not accustomed to associating with images. These include ultrasound,
electron microscopy, and computer-generated images.Thus, digital image
processing encompasses a wide and varied field of applications.
There is no general agreement among authors regarding where image processing
stops and other related areas, such as image analysis and computer vision,
start. Sometimes a distinction is made by defining image processing as a
discipline in which both the input and output of a process are images.We believe
this to be a limiting and somewhat artificial boundary. For example, under this
definition, even the trivial task of computing the average intensity of an image
(which yields a single number) would not be considered an image processing operation.
On the other hand, there are fields such as computer vision whose ultimate
goal is to use computers to emulate human vision, including learning
and being able to make inferences and take actions based on visual inputs.This
area itself is a branch of artificial intelligence (AI) whose objective is to emulate
human intelligence.The field of AI is in its earliest stages of infancy in terms
of development, with progress having been much slower than originally anticipated.
The area of image analysis (also called image understanding) is in between
image processing and computer vision.
There are no clear-cut boundaries in the continuum from image processing
at one end to computer vision at the other. However, one useful paradigm is
to consider three types of computerized processes in this continuum: low-,
mid-, and high-level processes. Low-level processes involve primitive operations
such as image preprocessing to reduce noise, contrast enhancement, and
image sharpening.A low-level process is characterized by the fact that both
its inputs and outputs are images. Mid-level processing on images involves
tasks such as segmentation (partitioning an image into regions or objects),
description of those objects to reduce them to a form suitable for computer
processing, and classification (recognition) of individual objects.A mid-level
process is characterized by the fact that its inputs generally are images, but its
outputs are attributes extracted from those images (e.g., edges, contours, and
the identity of individual objects). Finally, higher-level processing involves
“making sense” of an ensemble of recognized objects, as in image analysis,
and, at the far end of the continuum, performing the cognitive functions normally
associated with vision.
Based on the preceding comments, we see that a logical place of overlap between
image processing and image analysis is the area of recognition of individual
regions or objects in an image. Thus, what we call in this book digital
image processing encompasses processes whose inputs and outputs are images
† References in the Bibliography at the end of the book are listed in alphabetical order by authors’ last
names.
and, in addition, encompasses processes that extract attributes from images, up
to and including the recognition of individual objects. As a simple illustration
to clarify these concepts, consider the area of automated analysis of text. The
processes of acquiring an image of the area containing the text, preprocessing
that image, extracting (segmenting) the individual characters, describing the
characters in a form suitable for computer processing, and recognizing those
individual characters are in the scope of what we call digital image processing
in this book. Making sense of the content of the page may be viewed as being
in the domain of image analysis and even computer vision, depending on the
level of complexity implied by the statement “making sense.” As will become
evident shortly, digital image processing, as we have defined it, is used successfully
in a broad range of areas of exceptional social and economic value.The concepts
developed in the following chapters are the foundation for the methods
used in those application areas.
The Origins of Digital Image Processing
One of the first applications of digital images was in the newspaper industry,
when pictures were first sent by submarine cable between London and New
York. Introduction of the Bartlane cable picture transmission system in the
early 1920s reduced the time required to transport a picture across the Atlantic
from more than a week to less than three hours. Specialized printing equipment
coded pictures for cable transmission and then reconstructed them at the receiving
end. was transmitted in this way and reproduced on a telegraph
printer fitted with typefaces simulating a halftone pattern.
Some of the initial problems in improving the visual quality of these early digital
pictures were related to the selection of printing procedures and the distribution
of intensity levels. The printing method used to obtain Fig. 1.1 was
abandoned toward the end of 1921 in favor of a technique based on photographic
reproduction made from tapes perforated at the telegraph receiving
terminal. Figure 1.2 shows an image obtained using this method.The improvements
over Fig. 1.1 are evident, both in tonal quality and in resolution.