Digital Image Processing - Rafael C. Gonzalez and Paul Wintz - 2nd ed.

Description: Digital Image Processing Second Edition by Rafael C. Gonzalez and Paul Wintz Addison Wesley, 1987, 0201110261, Hardcover, Dust Jacket, VG/VG condition, no marks, no underlining, no highlighting, 503 pages. Since the first publication in 1977 of Digital Image Processing by Gonzalez and Wintz, this technology has experienced vigorous growth in fields ranging from medical and military applications to robot vision and automated industrial inspection. The continued rapid expansion of applications of digital image processing techniques prompted the authors to prepare a second edition of its highly successful predecessor. This new edition of Digital Image Processing contains extensive revisions and new material not found in the original text. FEATURES NEW TO THIS EDITION • Additional discussions on geometric relationships between pixels. • Arithmetic and logic operations via mask processing. • Imaging geometry section covering image translation, scaling, rotation, perspective transformations, camera modeling, and stereo imaging. • The Hough transform. • Local enhancement techniques. • Geometric transformations for image warping. • Recent reviews of data compression techniques. • New material on representation and description, including boundary descriptors, skeletonizing techniques, textural descriptors and descriptions of similarity. The mathematical level of the book continues to be well within the grasp of seniors in technical disciplines such as engineering or computer science who have had introductory preparation in mathematical analysis, matrix theory, probability, and computer programming. Practicing engineers and scientists with this background will find Digital Image Processing an ideal text for self. study. As in the first edition, the principal objectives of this book are to provide an introduction to basic concepts and methodologies for image processing, and to lay a foundation that can be used as the basis for further study, practice, and research in this field. Addison-Wesley Publishing Company ABOUT THE AUTHORS Rafael C. Gonzalez is a Distinguished Service Professor of Electrical Engineering at the University of Tennessee, Knoxville, and founder and president of Perceptics Corporation, a high-technology firm that specializes in image processing, pattern recognition, computer vision, and machine intelligence. He received his B.S. degree from the University of Miami, and his M.E. and Ph.D. degrees from the University of Florida, Gainesville, all in electrical engineering. Dr. Gonzalez is internationally known in his field, having authored or coauthored over 100 articles and four books dealing with image processing, pattern recognition, robotics, and computer vision. He received the 1978 UTK Chancellor's Research Scholar Award, the 1980 Magnavox Engineering Professor Award, and the 1980 M.E. Brooks Distinguished Professor Award for his work in these fields. In 1982 he was awarded an IBM Professorship at the University of Tennessee, and in 1984 he became a Distinguished Service Professor at that institution. In 1985 he was named a Distinguished Engineering Alumnus by the University of Miami. Dr. Gonzalez is a frequent consultant to industry and government and is a member of numerous engineering, professional and honorary societies, including Tau Beta Pi, Phi Kappa Phi, Eta Kappa Nu, and Sigma Xi. He is a Fellow of the IEEE. Paul Wintz, currently a consultant, was previously a Professor of Electrical Engineering at Purdue University and president of Wintek Corporation in Lafayette, Indiana. Prior to those assignments he worked as electronic countermeasures operator in the U.S. Army, and as an engineer for Duncan Electric Company. Dr. Wintz received his B.S., M.S., and Ph.D. degrees, all in electrical engineering, from Purdue University. He has served as a consultant for both government agencies and private industry and has assumed active responsibility in numerous professional societies, especially the IEEE. He is coauthor of three books and has contributed to five others, as well as publishing in IEEE transactions and other electrical engineering journals. Dr. Wintz is a member of Sigma Xi and Eta Kappa Nu. CONTENTS Chapter 1 INTRODUCTION 1.1 Background 1.2 Digital Image Representation 1.3 Elements of a Digital Image Processing System 1.3.1 Image Processors 1.3.2 Digitizers 1.3.3 Digital Computers 1.3.4 Storage Devices 1.3.5 Display and Recording Devices 1.4 Organization of the Book References Chapter 2 DIGITAL IMAGE FUNDAMENTALS 2.1 Elements of Visual Perception 2.1.1 Structure of the Human Eye 2.1.2 Image Formation in the Eye 2.1.3 Brightness Adaptation and Discrimination 2.2 An Image Model 2.3 Sampling and Quantization 2.3.1 Uniform Sampling and Quantization 2.3.2 Nonuniform Sampling and Quantization 2.4 Some Basic Relationships between Pixels 2.4.1 Neighbors of a Pixel 2.4.2 Connectivity 2.4.3 Distance Measures 2.4.4 Arithmetic/Logic Operations 2.5 Imaging Geometry 2.5.1 Some Basic Transformations 2.5.2 Perspective Transformations 2.5.3 Camera Model 2.5.4 Camera Calibration 2.5.5 Stereo Imaging 2.6 Photographic Film 2.6.1 Film Structure and Exposure 2.6.2 Film Characteristics 2.6.3 Diaphragm and Shutter Settings 2.7 Concluding Remarks References Problems Chapter 3 IMAGE TRANSFORMS 3.1 Introduction to the Fourier Transform 3.2 The Discrete Fourier Transform 3.3 Some Properties of the Two-Dimensional Fourier Transform 3.3. I Separability 3.3.2 Translation 3.3.3 Periodicity and Conjugate Symmetry 3.3.4 Rotation 3.3.5 Distributivity and Scaling 3.3.6 Average Value 3.3.7 Laplacian 3.3.8 Convolution and Correlation 3.3.9 Sampling 3.4 The Fast Fourier Transform 3.4.1 FFT Algorithm 3.4.2 Number of Operations 3.4.3 The Inverse FFT 3.4.4 Implementation 3.5 Other Separable Image Transforms 3.5.1 Walsh Transform 3.5.2 Hadamard Transform 3.5.3 Discrete Cosine Transform 3.6 The Hotelling Transform 3.6. I Formulation 3.6.2 Application to Image Rotation 3.7 The Hough Transform 3.8 Concluding Remarks References Problems Chapter 4 IMAGE ENHANCEMENT 4.1 Background 4. 1 . I Spatial-Domain Methods 4.1.2 Frequency-Domain Methods 4.2 Image Enhancement by Histogram-Modification Techniques 4.2.I Foundation 4.2.2 Histogram Equalization 4.2.3 Direct Histogram Specification 4.2.4 Local Enhancement 4.3 Image Smoothing 4.3.1 Neighborhood Averaging 4.3.2 Median Filtering 4.3.3 Lowpass Filtering 4.3.4 Averaging of Multiple Images 4.4 Image Sharpening 4.4.1 Sharpening by Differentiation 4.4.2 Highpass Filtering 4.5 Enhancement Based on an Image Model 4.6 Generation of Spatial Masks from Frequency-Domain Specifications 4.7 Pseudo-Color Image Processing 4.7.1 Color Fundamentals 4.7.2 Density Slicing 4.7.3 Gray-Level-to-Color Transformations 4.7.4 A Filtering Approach 4.8 Concluding Remarks References Problems Chapter 5 IMAGE RESTORATION 5.1 Degradation Model 5. I . I Some Definitions 5.1.2 Degradation Model for Continuous Functions 5.1.3 Discrete Formulation 5.2 Diagonalization of Circulant and Block-Circulant Matrices 5.2.1 Circulant Matrices 5.2.2 Block-Circulant Matrices 5.2.3 Effects of Diagonalization on the Degradation Model 5.3 Algebraic Approach to Restoration 5.3.1 Unconstrained Restoration 5.3.2 Constrained Restoration 5.4 Inverse Filtering 5.4.I Formulation 5.4.2 Removal of Blur Caused by Uniform Linear Motion 5.5 Least-Mean-Square (Wiener) Filter 5.6 Constrained Least-Squares Restoration 5.7 Interactive Restoration 5.8 Restoration in the Spatial Domain 5.9 Geometric Transformations 5.9.1 Spatial Transformations 5.9.2 Gray-Level Interpolation 5.10 Concluding Remarks References Problems Chapter 6 IMAGE ENCODING 6.1 Fidelity Criteria 6.1.1 Objective Fidelity Criteria 6.1.2 Subjective Fidelity Criteria 6.2 The Encoding Process 6.2.1 The Mapping 6.2.2 The Quantizer 6.2.3 The Coder 6.3 Error-Free Encoding 6.3.1 Example I. Differential Encoding for Storage of LANDSAT Imagery 6.3.2 Example 2. Contour Encoding 6.3.3 Example 3. Run-Length Encoding for Flood Maps 6.4 Image Encoding Relative to a Fidelity Criterion 6.4.1 Example 1. Differential Pulse Code Modulation (DPCM) 6.4.2 Example 2. Transform Encoding 6.4.3 Example 3. Hybrid Encoding for RPV TV 6.5 Use of the Mapper Outputs as Features 6.6 Concluding Remarks References Problems Chapter 7 IMAGE SEGMENTATION 7.1 The Detection of Discontinuities 7.1.1 Point Detection 7.1.2 Line Detection 7.1.3 Edge Detection 7.1.4 Combined Detection 7.2 Edge Linking and Boundary Detection 7.2.1 Local Analysis 7.2.2 Global Analysis via the Hough Transform 7.2.3 Global Analysis via Graph-Theoretic Techniques 7.3 Thresholding 7.3.I Foundation 7.3.2 The Role of illumination 7.3.3 A Global Thresholding Technique 7.3.4 Optimal Thresholding 7.3.5 Threshold Selection Based on Boundary Characteristics 7.3.6 Thresholds Based on Several Variables 7.4 Region-Oriented Segmentation 7.4.1 Basic Formulation 7.4.2 Region Growing by Pixel Aggregation 7.4.3 Region Splitting and Merging 7.5 The Use of Motion in Segmentation 7.5.1 Spatial Techniques 7.5.2 Frequency-Domain Techniques 7.6 Concluding Remarks References Problems Chapter 8 REPRESENTATION AND DESCRIPTION 8.1 Representation Schemes 8.1.1 Chain Codes 8.1.2 Polygonal Approximations 8.1.3 Signatures 8.1.4 Boundary Segments 8.1.5 The Skeleton of a Region 8.2 Boundary Descriptors 8.2.1 Some Simple Descriptors 8.2.2 Shape Numbers 8.2.3 Fourier Descriptors 8.2.4 Moments 8.3 Regional Descriptors 8.3.1 Some Simple Descriptors 8.3.2 Topological Descriptors 8.3.3 Texture 8.3.4 Moments 8.4 Descriptions of Similarity 8.4.1 Distance Measures 8.4.2 Correlation 8.4.3 Boundary Matching 8.5 Relational Descriptions 8.5.1 String Grammars and Languages 8.5.2 Higher-Dimensional Grammars 8.6 Concluding Remarks References Problems Appendix A IMAGE DISPLAY SUBROUTINES Appendix B CODED IMAGES BIBLIOGRAPHY INDEX nthdegree books

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