Digital ImageProcessingThird EditionRafael C. GonzalezUniversity of TennesseeRichard E. WoodsMedData InteractiveUpper Saddle River, NJ 07458GONZ_FMv3.qxd 7/26/07 9:05 AM Page iLibrary of Congress Cataloging-in-Publication Data on FileVice President and Editorial Director, ECS: Marcia J. HortonExecutive Editor: Michael McDonaldAssociate Editor: Alice DworkinEditorial Assistant: William OpaluchManaging Editor: Scott DisannoProduction Editor: Rose KernanDirector of Creative Services: Paul BelfantiCreative Director: Juan LopezArt Director: Heather ScottArt Editors: Gregory Dulles and Thomas BenfattiManufacturing Manager: Alexis Heydt-LongManufacturing Buyer: Lisa McDowellSenior Marketing Manager: Tim Galligan© 2008 by Pearson Education, Inc.Pearson Prentice HallPearson Education, Inc.Upper Saddle River, New Jersey 07458All rights reserved. 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Ltd.Pearson Education, Inc., Upper Saddle River, New JerseyGONZ_FMv3.qxd 7/26/07 9:05 AM Page iiIntroductionPreviewInterest in digital image processing methods stems from two principal applica-tion areas: improvement of pictorial information for human interpretation; andprocessing of image data for storage, transmission, and representation for au-tonomous machine perception.This chapter has several objectives: (1) to definethe 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 you an idea of the state of the artin 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 thebooks 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, , where x andy 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. Whenx, y, and the intensity values of f are all finite, discrete quantities, we call theimage a digital image.The field of digital image processing refers to processingdigital 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 locationf(x, y)1One picture is worth more than ten thousand words.Anonymous1GONZ_CH01v5.qxd 7/10/07 11:57 AM Page 12 Chapter 1 ■ Introductionand value. These elements are called picture elements, image elements, pels, andpixels. Pixel is the term used most widely to denote the elements of a digitalimage. 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 imagesplay the single most important role in human perception. However, unlike hu-mans, who are limited to the visual band of the electromagnetic (EM) spec-trum, imaging machines cover almost the entire EM spectrum, ranging fromgamma to radio waves. They can operate on images generated by sources thathumans are not accustomed to associating with images. These include ultra-sound, electron microscopy, and computer-generated images. Thus, digitalimage processing encompasses a wide and varied field of applications.There is no general agreement among authors regarding where imageprocessing stops and other related areas, such as image analysis and comput-er vision, start. Sometimes a distinction is made by defining image processingas a discipline in which both the input and output of a process are images.Webelieve this to be a limiting and somewhat artificial boundary. For example,under this definition, even the trivial task of computing the average intensityof an image (which yields a single number) would not be considered animage processing operation. On the other hand, there are fields such as com-puter vision whose ultimate goal is to use computers to emulate human vi-sion, including learning and being able to make inferences and take actionsbased 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 inits earliest stages of infancy in terms of development, with progress havingbeen much slower than originally anticipated. The area of image analysis(also called image understanding) is in between image processing and com-puter vision.There are no clear-cut boundaries in the continuum from image processingat one end to computer vision at the other. However, one useful paradigm isto 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, andimage sharpening. A low-level process is characterized by the fact that bothits inputs and outputs are images. Mid-level processing on images involvestasks such as segmentation (partitioning an image into regions or objects), de-scription of those objects to reduce them to a form suitable for computer pro-cessing, and classification (recognition) of individual objects. A mid-levelprocess is characterized by the fact that its inputs generally are images, but itsoutputs are attributes extracted