《Digital Image Processing》Second Edition，Rafael C. Gonzalez Richard E. Woods

GONZFM-i-xxii. 5-10-2001 14:22 Page xxii

Introduction One picture is worth more than ten thousand word Preview Interest in digital image processing methods stems from two principal applica- tion areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for au- tonomous 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 per spective 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 ap- plied; (4)to discuss briefly the principal approaches used in digital image pro- cessing;(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 1.1 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 coordi nates(x, y) is called the intensity or gray level of the image at that point. When 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 com posed of a finite number of elements, each of which has a particular location and

1 1 Introduction One picture is worth more than ten thousand words. Anonymous Preview Interest in digital image processing methods stems from two principal applica￾tion areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for au￾tonomous 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 per￾spective 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 ap￾plied; (4) to discuss briefly the principal approaches used in digital image pro￾cessing; (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 coordi￾nates (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 com￾posed of a finite number of elements, each of which has a particular location and 1.1 GONZ01-001-033.II 29-08-2001 14:42 Page 1

2 Chapter 1 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 digi tal 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) spec trum, 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 ultra- sound, 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 pro cessing stops and other related areas, such as image analysis and computer sion, 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 op eration. On the other hand, there are fields such as computer vision whose ul timate 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(Al) whose objective is to emu late 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 antic ipated. The area of image analysis(also called image understanding) is in be- tween 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 opera- tions 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 nor- mally associated with vision. Based on the preceding comments, we see that a logical place of overlap be- ween image processing and image analysis is the area of recognition of indi vidual regions or objects in an image. Thus, what we call in this book digital image processing encompasses processes whose inputs and outputs are images

2 Chapter 1 ■ 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 digi￾tal 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) spec￾trum, 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 ultra￾sound, 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 pro￾cessing stops and other related areas, such as image analysis and computer vi￾sion, 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 op￾eration. On the other hand, there are fields such as computer vision whose ul￾timate 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 emu￾late 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 antic￾ipated. The area of image analysis (also called image understanding) is in be￾tween 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 opera￾tions 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 nor￾mally associated with vision. Based on the preceding comments, we see that a logical place of overlap be￾tween image processing and image analysis is the area of recognition of indi￾vidual regions or objects in an image. Thus, what we call in this book digital image processing encompasses processes whose inputs and outputs are images GONZ01-001-033.II 29-08-2001 14:42 Page 2

1.2 The Origins of Digital Image Processing 3 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 success fully in a broad range of areas of exceptional social and economic value. The con cepts developed in the following chapters are the foundation for the methods used in those application areas. 1.2 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 Nev 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 ded pictures for cable transmission and then reconstructed them at the re ceiving end. Figure 1. 1 was transmitted in this way and reproduced on a tele- graph printer fitted with typefaces simulating a halftone patter Some of the initial problems in improving the visual quality of these early ital pictures were related to the selection of printing procedures and the di bution 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 photo graphic reproduction made from tal rforated at the tel terminal Figure 1.2 shows an image obtained using this method. The improve- ments over Fig 1.1 are evident, both in tonal quality and in resolution RE1.1 digital picture produced in 1921 v ate References in the Bibliography at the end of the book are listed in alphabetical order by authors' last

1.2 ■ The Origins of Digital Image Processing 3 †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 success￾fully in a broad range of areas of exceptional social and economic value.The con￾cepts 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 re￾ceiving end. Figure 1.1 was transmitted in this way and reproduced on a tele￾graph printer fitted with typefaces simulating a halftone pattern. Some of the initial problems in improving the visual quality of these early dig￾ital pictures were related to the selection of printing procedures and the distri￾bution 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 photo￾graphic reproduction made from tapes perforated at the telegraph receiving terminal. Figure 1.2 shows an image obtained using this method. The improve￾ments over Fig. 1.1 are evident, both in tonal quality and in resolution. 1.2 FIGURE 1.1 A digital picture produced in 1921 from a coded tape by a telegraph printer with special type faces. (McFarlane.† ) GONZ01-001-033.II 29-08-2001 14:42 Page 3

4 Chapter 1 Introduction FIGURE12A ade in 1922 unched after the signals had Atlantic twice Some errors are McFarlane The early Bartlane systems were capable of coding images in five distinct levels of gray. This capability was increased to 15 levels in 1929. Figure 1.3 is typical of the type of images that could be obtained using the 15-tone equipment During this period, introduction of a system for developing a film plate via light beams that were modulated by the coded picture tape improved the reproduc tion process considerably Although the examples just cited involve digital images, they are not con- idered digital image processing results in the context of our definition because computers were not involved in their creation. Thus, the history of digital image processing is intimately tied to the development of the digital computer. In fact digital images require so much storage and computational power that progress in the field of digital image processing has been dependent on the development of digital computers and of supporting technologies that include data storage, display, and transmission The idea of a computer goes back to the invention of the abacus in Asia Minor, more than 5000 years ago. More recently, there were developments in the past two centuries that are the foundation of what we call a computer today However, the basis for what we call a modern digital computer dates back to only the 1940s with the introduction by John von Neumann of two key concepts (1)a memory to hold a stored program and data, and(2)conditional branch- ing. These two ideas are the foundation of a central processing unit( CPU) which is at the heart of computers today. Starting with von Neumann, there were FIGURE 1.3 Unretouched cable picture of Generals pershing and Foch transmitted in 1929 from London to new York by 15-tone ent

4 Chapter 1 ■ Introduction FIGURE 1.3 Unretouched cable picture of Generals Pershing and Foch, transmitted in 1929 from London to New York by 15-tone equipment. (McFarlane.) The early Bartlane systems were capable of coding images in five distinct levels of gray. This capability was increased to 15 levels in 1929. Figure 1.3 is typical of the type of images that could be obtained using the 15-tone equipment. During this period, introduction of a system for developing a film plate via light beams that were modulated by the coded picture tape improved the reproduc￾tion process considerably. Although the examples just cited involve digital images, they are not con￾sidered digital image processing results in the context of our definition because computers were not involved in their creation.Thus, the history of digital image processing is intimately tied to the development of the digital computer. In fact, digital images require so much storage and computational power that progress in the field of digital image processing has been dependent on the development of digital computers and of supporting technologies that include data storage, display, and transmission. The idea of a computer goes back to the invention of the abacus in Asia Minor, more than 5000 years ago. More recently, there were developments in the past two centuries that are the foundation of what we call a computer today. However, the basis for what we call a modern digital computer dates back to only the 1940s with the introduction by John von Neumann of two key concepts: (1) a memory to hold a stored program and data, and (2) conditional branch￾ing. These two ideas are the foundation of a central processing unit (CPU), which is at the heart of computers today. Starting with von Neumann, there were FIGURE 1.2 A digital picture made in 1922 from a tape punched after the signals had crossed the Atlantic twice. Some errors are visible. (McFarlane.) GONZ01-001-033.II 29-08-2001 14:42 Page 4