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Handbook of Image and Video Processing, 2nd Edition

Book Description

55% new material in the latest edition of this “must-have” for students and practitioners of image & video processing!

This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource.

• Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms
• Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula
• Covers the various image and video processing standards that exist and are emerging, driving today’s explosive industry
• Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived
• Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data
• Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader’s own potential applications

About the Editor…
Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.

* No other resource for image and video processing contains the same breadth of up-to-date coverage
* Each chapter written by one or several of the top experts working in that area
* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various,
image-intensive disciplines

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Preface
  6. Editor
  7. Contributors
  8. SECTION I: Introduction
    1. Introduction
    2. Chapter 1.1: Introduction to Digital Image and Video Processing
      1. Types of Images
      2. Scale of Images
      3. Dimension of Images
      4. Digitization of Images
      5. Sampled Images
      6. Quantized Images
      7. Color Images
      8. Size of Image Data
      9. Digital Video
      10. Sampled Video
      11. Video Transmission
      12. Objectives of this Handbook
      13. Organization of the Handbook
      14. Acknowledgment
  9. SECTION II: Basic Image Processing Techniques
    1. Introduction to Basic Image Processing Techniques
    2. Chapter 2.1: Basic Gray-Level Image Processing
      1. 1 Introduction
      2. 2 Notation
      3. 3 Image Histogram
      4. 4 Linear Point Operations on Images
      5. 5 Nonlinear Point Operations on Images
      6. 6 Arithmetic Operations Between Images
      7. 7 Geometric Image Operations
    3. Chapter 2.2: Basic Binary Image Processing
      1. 1 Introduction
      2. 2 Image Thresholding
      3. 3 Region Labeling
      4. 4 Binary Image Morphology
      5. 5 Binary Image Representation and Compression
    4. Chapter 2.3: Basic Tools for Image Fourier Analysis
      1. 1 Introduction
      2. 2 Discrete-Space Sinusoids
      3. 3 Discrete-Space Fourier Transform
      4. 4 Two-Dimensional Discrete Fourier Transform
      5. 5 Understanding Image Frequencies and the Discrete Fourier Transform
      6. 6 Related Topics in this Handbook
    5. Chapter 2.4: Image Processing Education
      1. 1 Introduction
      2. 2 IP-LAB: A Tool for Teaching Image-Processing Programming in Java Using ImageJ
      3. 3 Java-based Educational Software for Image and Two-Dimensional Signal Processing
      4. 4 SIVA — The Signal, Image, and Video Audio-Visualization Gallery
      5. 5 VcDemo — The Image and Video Compression Learning Tool
      6. 6 Conclusions
  10. SECTION III: Image and Video Processing
    1. Introduction to Image and Video Processing
    2. Chapter 3.1: Basic Linear Filtering with Application to Image Enhancement
      1. 1 Introduction
      2. 2 Impulse Response, Linear Convolution, and Frequency Response
      3. 3 Linear Image Enhancement
      4. 4 Discussion
    3. Chapter 3.2: Nonlinear Filtering for Image Analysis and Enhancement
      1. 1 Introduction
      2. 2 Weighted Median Smoothers and Filters
      3. 3 Image Noise Cleaning
      4. 4 Image Zooming
      5. 5 Image Sharpening
      6. 6 Edge Detection
      7. 7 Conclusion
      8. Acknowledgment
    4. Chapter 3.3: Morphological Filtering for Image Enhancement and Feature Detection
      1. 1 Introduction
      2. 2 Morphologic Image Operators
      3. 3 Morphologic Filters for Image Enhancement
      4. 4 Morphologic Operators for Template Matching
      5. 5 Morphologic Operators for Feature Detection
      6. 6 Optimal Design of Morphologic Filters for Enhancement
      7. 7 Conclusions
      8. Acknowledgment
    5. Chapter 3.4: Wavelet Denoising for Image Enhancement
      1. 1 Introduction
      2. 2 Wavelet Shrinkage Denoising
      3. 3 Image Enhancement via Wavelet Shrinkage
      4. 4 Examples
      5. 5 Image Denoising Using Natural Scene Statistics
      6. 6 Summary
    6. Chapter 3.5: Basic Methods for Image Restoration and Identification
      1. 1 Introduction
      2. 2 Blur Models
      3. 3 Image Restoration Algorithms
      4. 4 Blur Identification Algorithms
      5. Expectation step:
      6. Maximization step:
    7. Chapter 3.6: Regularization in Image Restoration and Reconstruction
      1. 1 Introduction
      2. 2 Direct Regularization Methods
      3. 3 Iterative Regularization Methods
      4. 4 Regularization Parameter Choice
      5. 5 Summary
    8. Chapter 3.7: Multichannel Image Recovery
      1. 1 Introduction
      2. 2 Imaging Model
      3. 3 Multichannel Image Estimation Approaches
      4. 4 Explicit Multichannel Recovery Approaches
      5. 5 Implicit Approach to Multichannel Image Recovery
      6. Acknowledgments
    9. Chapter 3.8: Multi-Frame Image Restoration
      1. 1 Introduction
      2. 2 Mathematic Models
      3. 3 The Multi-Frame Restoration Problem
      4. 4 Nuisance Parameters and Blind Restoration
      5. 5 Applications
      6. Acknowledgments
    10. Chapter 3.9: Iterative Image Restoration
      1. 1 Introduction
      2. 2 Iterative Recovery Algorithms
      3. 3 Spatially Invariant Degradation
      4. 4 Matrix-Vector Formulation
      5. 5 Use of Constraints
      6. 6 Additional Considerations
      7. 7 Discussion
    11. Chapter 3.10: Motion Detection and Estimation
      1. 1 Introduction
      2. 2 Notation and Preliminaries
      3. 3 Motion Detection
      4. 4 Motion Estimation
      5. 5 Practical Motion Estimation Algorithms
      6. 6 Perspectives
      7. 7 Acknowledgments
    12. Chapter 3.11: Video Enhancement and Restoration
      1. 1 Introduction
      2. 2 Spatio-Temporal Noise Filtering
      3. 3 Blotch Detection and Removal
      4. 4 Vinegar Syndrome Removal
      5. 5 Intensity Flicker Correction
      6. 6 Kinescope Moiré Removal
      7. 7 Concluding Remarks
    13. Chapter 3.12: Local and Global Stereo Methods
      1. 1 Introduction
      2. 2 Background of Computational Stereo Vision
      3. 3 A Taxonomy of Stereo Correspondence Algorithms
      4. 4 Conclusion
      5. Acknowledgment
    14. Chapter 3.13: Image Sequence Stabilization, Mosaicking, and Superresolution
      1. 1 Introduction
      2. 2 Biologic Motivation: Insect Navigation
      3. 3 Global Motion Models
      4. 4 Algorithm
      5. 5 Two-Dimensional Stabilization
      6. 6 Mosaicking
      7. 7 Motion Superresolution
      8. 8 Three-Dimensional Stabilization
      9. 9 Summary
  11. SECTION IV: Image and Video Analysis
    1. Introduction to Image and Video Analysis
    2. Chapter 4.1: Computational Models of Early Human Vision
      1. 1 Introduction
      2. 2 The Front End
      3. 3 Early Filtering and Parallel Pathways
      4. 4 The Primary Visual Cortex and Fundamental Properties of Vision
      5. 5 Concluding Remarks
    3. Chapter 4.2: Multiscale Image Decompositions and Wavelets
      1. 1 Overview
      2. 2 Pyramid Representations
      3. 3 Wavelet Representations
      4. 4 Other Multiscale Decompositions
      5. 5 Conclusion
      6. Acknowledgment
    4. Chapter 4.3: Random Field Models
      1. 1 Introduction
      2. 2 Random Fields — Overview
      3. 3 Multiscale Random Fields
      4. 4 A Nonlinear/Non-Gaussian Model: the Gaussian Mixture
      5. Acknowledgment
    5. Chapter 4.4: AM-FM Image Models: Fundamental Techniques and Emerging Trends
      1. 1 Introduction
      2. 2 Fundamentals of AM-FM Image Modeling
      3. 3 Practical Techniques for AM-FM Image Modeling
      4. 4 Emerging Trends in AM-FM Image Modeling
      5. 5 Conclusion
      6. Acknowledgment
    6. Chapter 4.5: Image Noise Models
      1. 1 Summary
      2. 2 Preliminaries
      3. 3 Elements of Estimation Theory
      4. 4 Types of Noise and Where They Might Occur
      5. 5 CCD Imaging
      6. 6 Speckle
      7. 7 Conclusions
    7. Chapter 4.6: Color and Multispectral Image Representation and Display
      1. 1 Introduction
      2. 2 Preliminary Notes on Display of Images
      3. 3 Notation and Prerequisite Knowledge
      4. 4 Analog Images as Physical Functions
      5. 5 Colorimetry
      6. 6 Sampling of Color Signals and Sensors
      7. 7 Color I/O Device Calibration
      8. 8 Summary and Future Outlook
      9. Acknowledgment
    8. Chapter 4.7: Statistical Modeling of Photographic Images
      1. 1 Introduction
      2. 2 The Gaussian Model
      3. 3 Wavelet Marginal Models
      4. 4 Wavelet Joint Models
      5. 5 Discussion
    9. Chapter 4.8: Statistical Methods for Image Segmentation
      1. 1 Introduction
      2. 2 Image Segmentation: The Mathematic Problem
      3. 3 Image Statistics for Segmentation
      4. 4 Statistical Image Segmentation
      5. 4.2 Aerial Image Segmentation
      6. 5 Discussion
    10. Chapter 4.9: Multiband Techniques for Texture Classification and Segmentation
      1. 1 Introduction
      2. 2 Gabor Functions
      3. 3 Microfeature Representation
      4. 4 The Texture Model
      5. 5 Experimental Results
      6. 6 Image Segmentation Using Texture
      7. 7 Image Retrieval Using Texture
      8. 8 Texture Motifs
      9. 9 Summary
      10. Acknowledgments
    11. Chapter 4.10: Video Segmentation
      1. 1 Introduction
      2. 2 Scene Change Detection
      3. 3 Spatio-Temporal Change Detection
      4. 4 Motion Segmentation
      5. 5 Simultaneous Motion Estimation and Segmentation
      6. 6 Semantic Video Object Segmentation
      7. 7 Examples
      8. Acknowledgments
    12. Chapter 4.11: 2D and 3D Motion Tracking in Digital Video
      1. 1 Introduction
      2. 2 Rigid Object Tracking
      3. 3 Articulated Object Tracking
      4. Acknowledgment
    13. Chapter 4.12: Adaptive and Neural Methods for Image Segmentation
      1. 1 Introduction
      2. 2 Artificial Neural Networks
      3. 3 Perceptual Grouping and Edge-based Segmentation
      4. 4 Adaptive Multichannel Modeling for Texture-based Segmentation
      5. 5 An Optimization Framework
      6. 6 Image Segmentation via Adaptive Clustering
      7. 7 Oscillation-based Segmentation
      8. 8 Integrated Segmentation and Recognition
      9. 9 Concluding Remarks
      10. Acknowledgments
    14. Chapter 4.13: Gradient and Laplacian Edge Detection
      1. 1 Introduction
      2. 2 Gradient-based Methods
      3. 3 Laplacian-based Methods
      4. 4 Canny’s Method
      5. 5 Approaches for Color and Multispectral Images
      6. 6 Summary
    15. Chapter 4.14: Diffusion Partial Differential Equations for Edge Detection
      1. 1 Introduction and Motivation
      2. 2 Background on Diffusion
      3. 3 Anisotropic Diffusion Techniques
      4. 4 Application of Anisotropic Diffusion to Edge Detection
      5. 5 Using Vector Diffusion and Parametric Active Contours to Locate Edges
      6. 6 Conclusions
    16. Chapter 4.15: Shape Smoothing and PDEs
      1. 1 Principles for Shape Smoothing
      2. 2 Algorithm 1: Dynamic Shape
      3. 3 Algorithm 2: Iterated Weighted Median Filter
      4. 4 Algorithm 3: Heat Equation on Curves
      5. 5 Algorithm 4: Renormalized Heat Equation on Curves
      6. 6 Algorithm 5: Iterated Affine Erosion
      7. 7 Bibliographic Notes
      8. Acknowledgments
    17. Chapter 4.16: PDEs for Morphological Scale Spaces and Eikonal Applications
      1. 1 Introduction
      2. 2 Multidimensional Morphologic Systems and Slope Transforms
      3. 3 Partial Differential Equations for Morphologic Scale Spaces
      4. 4 Curve Evolution, Level Sets, and Morphologic Flows
      5. 5 Distance Transforms
      6. 6 Eikonal Partial Differential Equation and Distance Propagation
      7. 7 Applications of Eikonal Partial Differential Equation
      8. 8 Conclusions
      9. Acknowledgments
    18. Chapter 4.17: Geometric Active Contours for Image Segmentation
      1. 1 Introduction
      2. 2 Mathematic Notations and Problem Formulation
      3. 3 From Edge Detectors to Geometric Evolutions
      4. 4 Calculus of Variations for Geometric Measures
      5. 5 Gradient Descent in Level Set Formulation
      6. 6 Efficient Numeric Schemes
      7. 7 Examples
      8. 8 Additional Comments on Related Developments
      9. 9 Summary
      10. Acknowledgments
    19. Chapter 4.18: Software for Image and Video Processing
      1. 1 Introduction
      2. 2 Algorithm Development Environments
      3. 3 Compiled Libraries
      4. 4 Source Code
      5. 5 Specialized Processing and Visualization Environments
      6. 6 Other Software
      7. 7 Conclusion
      8. Acknowledgements
  12. SECTION V: Image Compression
    1. Introduction to Image Compression
    2. Chapter 5.1: Lossless Coding
      1. 1 Introduction
      2. 2 Basics of Lossless Image Coding
      3. 3 Lossless Symbol Coding
      4. 4 Lossless Coding Standards
      5. 5 Other Developments in Lossless Coding
    3. Chapter 5.2: Block Truncation Coding (BTC)
      1. 1 Introduction and Historic Overview
      2. 2 Basics of BTC
      3. 3 Moment Preserving Quantization
      4. 4 Variations and Applications of BTC
      5. 5 Conclusions
      6. Acknowledgments
    4. Chapter 5.3: Fundamentals of Vector Quantization
      1. 1 Introduction
      2. 2 Theory of Vector Quantization
      3. 3 Design of Vector Quantizers
      4. 4 Vector Quantization Implementations
      5. 5 Structured Vector Quantization
      6. 6 Mean-Removed Vector Quantization
      7. 7 Multistage Vector Quantization
      8. 8 Trellis-Coded Vector Quantization
      9. 9 Closing Remarks
    5. Chapter 5.4: Wavelet Image Compression
      1. 1 What Are Wavelets: Why Are They Good for Image Coding?
      2. 2 The Compression Problem
      3. 3 The Transform Coding Paradigm
      4. 4 Subband Coding: The Early Days
      5. 5 New and More Efficient Class of Wavelet Coders
      6. 6 Adaptive Wavelet Transforms: Wavelet Packets
      7. 7 JPEG2000 and Recent Developments
      8. 8 Conclusion
    6. Chapter 5.5: Lossy Image Compression: JPEG and JPEG2000 Standards
      1. 1 Introduction
      2. 2 Lossy JPEG Codec Structure
      3. 3 Discrete Cosine Transform
      4. 4 Quantization
      5. 5 Coefficient-to-Symbol Mapping and Coding
      6. 6 Image Data Format and Components
      7. 7 Alternative Modes of Operation
      8. 8 JPEG Part 3
      9. 9 The JPEG2000 Standard
      10. 10 The JPEG2000 Part 1: Coding Architecture
      11. 11 JPEG2000 Performance and Extensions
      12. 12 Additional Information
    7. Chapter 5.6: The JPEG Lossless Image Compression Standards
      1. 1 Introduction
      2. 2 The Original JPEG Lossless Standards
      3. 3 JPEG-LS Lossless Compression Standard
      4. 4 JPEG2000 and the Integration of Lossless and Lossy Compression
      5. 5 Discussion
      6. 6 Additional Information
    8. Chapter 5.7: Multispectral Image Coding
      1. 1 Introduction
      2. 2 Lossy Compression
      3. 3 Lossless Compression
      4. 4 Conclusion
    9. Chapter 5.8: Recovery Methods for Postprocessing of Compressed Images
      1. 1 Introduction
      2. 2 Basic Theory of Projections onto Convex Sets
      3. 3 Projections onto Convex Sets-Based Image Recovery from Compressed Data
      4. 4 Maximum A Posteriori Estimation for Postprocessing of Compressed Images
      5. 5 Conclusions
  13. SECTION VI: Video Compression
    1. Introduction to Video Compression
    2. Chapter 6.1: Basic Concepts and Techniques of Video Coding and the H.261 Standard
      1. 1 Introduction
      2. 2 Introduction to Video Compression
      3. 3 Video Compression Application Requirements
      4. 4 Digital Video Signals and Formats
      5. 5 Video Compression Techniques
      6. 6 Video Encoding Standards and H.261
      7. 7 Closing Remarks
    3. Chapter 6.2: Interframe Subband/Wavelet Scalable Video Coding
      1. 1 Introduction
      2. 2 Motion Estimation
      3. 3 MC Temporal Filtering
      4. 4 Overlapped Block Motion Compensation
      5. 5 Scalable Motion Vector Coding
      6. 6 The EZBC Coder
      7. 7 Comparing Scalable Coders—Cross-Check Method
      8. 8 Multiple Adaptations
      9. 9 Some Visual Results
      10. 10 Other Improvements and Related Coders
      11. 11 Conclusions
    4. Chapter 6.3: Digital Video Transcoding
      1. 1 Introduction
      2. 2 Video Transcoding for Bit Rate Reduction
      3. 3 Heterogeneous Video Transcoding
      4. 4 Bit Rate Control in Video Transcoding
      5. 5 Error-Resilient Video Transcoding
      6. 6 Concluding Remarks
    5. Chapter 6.4: MPEG-1 and MPEG-2 Video Standards
      1. 1 MPEG-1 Video Coding Standard
      2. 2 MPEG-2 Video Coding Standard
    6. Chapter 6.5: MPEG-4, H.264/AVC, and MPEG-7: New Standards for the Digital Video Industry
      1. 1 Introduction
      2. 2 Terminology
      3. 3 MPEG-4: Technical Description
      4. 4 MPEG-7: Technical Description
      5. 5 Conclusions
    7. Chapter 6.6: Embedded Video Codecs
      1. 1 Introduction
      2. 2 Block-based Video Coding
      3. 3 Embedded Video Codec Design Requirements and Constraints
      4. 4 Embedded Video Codec Design Flow
      5. 5 Summary
  14. SECTION VII: Image and Video Acquisition
    1. Introduction to Image and Video Acquisition
    2. Chapter 7.1: Image Scanning, Sampling, and Interpolation
      1. 1 Image Capture
      2. 2 Fourier Analysis of Image Capture
      3. 3 Sampling Rate Conversion
      4. 4 Image Interpolation
      5. 5 Conclusion
    3. Chapter 7.2: Video Sampling and Interpolation
      1. 1 Introduction
      2. 2 Spatiotemporal Sampling Structures
      3. 3 Sampling and Reconstruction of Continuous Time-Varying Imagery
      4. 4 Sampling Structure Conversion
      5. 5 Conclusion
      6. Further Information
  15. SECTION VIII: Image and Video Rendering and Assessment
    1. Introduction to Image and Video Rendering and Assessment
    2. Chapter 8.1: Image Quantization, Halftoning, and Printing
      1. 1 Introduction and Printing Technologies
      2. 2 Scalar Quantization
      3. 3 Halftoning
      4. 4 Color Quantization
      5. 5 Halftone Watermarking and Embedding
      6. 6 Conclusion
    3. Chapter 8.2: Perceptual Criteria for Image Quality Evaluation
      1. 1 Introduction
      2. 2 Fundamentals of Human Perception and Image Quality
      3. 3 Visual Models for Image Quality and Compression
      4. 4 Conclusions
    4. Chapter 8.3: Structural Approaches to Image Quality Assessment
      1. 1 Introduction
      2. 2 The Structural Similarity Index
      3. 3 Image-Quality Assessment Using a Structural Similarity Index
      4. 4 Validating Image-Quality Measures
      5. 5 Concluding Remarks
    5. Chapter 8.4: Information Theoretic Approaches to Image Quality Assessment
      1. 1 Introduction
      2. 2 Mathematic Preliminaries
      3. 3 Information Fidelity for Quality Assessment of Natural Images
      4. 4 Implementation Issues
      5. 5 Results
      6. 6 Conclusions and Future Work
  16. SECTION IX: Image and Video Storage, Retrieval, and Communication
    1. Introduction to Image and Video Storage, Retrieval, and Communication
    2. Chapter 9.1: Image and Video Indexing and Retrieval
      1. 1 Introduction
      2. 2 Image and Video Features
      3. 3 From Low-Level Features to High-Level Semantics
      4. 4 Retrieval Techniques
      5. 5 Video Access and Browsing
      6. 6 The MPEG-7 Standard
      7. 7 Conclusion
    3. Chapter 9.2: A Unified Framework for Video Summarization, Browsing, and Retrieval
      1. 1 Introduction
      2. 2 Terminology
      3. 3 Video Analysis
      4. 4 Video Representation
      5. 5 Video Browsing and Retrieval
      6. 6 Proposed Framework
      7. 7 Conclusions and Promising Research Directions
      8. Acknowledgment
    4. Chapter 9.3: Video Communication Networks
      1. 1 Introduction
      2. 2 Video Compression Standards
      3. 3 Video Communication Networks
      4. 4 Internet Protocol Networks
      5. 5 Summary
    5. Chapter 9.4: Joint Source-Channel Coding for Video Communications
      1. 1 Introduction
      2. 2 On Joint Source-Channel Coding
      3. 3 Video Compression and Transmission
      4. 4 Channel Coding
      5. 5 Joint Source-Channel Coding
      6. 6 Discussion
    6. Chapter 9.5: Watermarking Techniques for Image Authentication and Copyright Protection
      1. 1 Introduction
      2. 2 Applications of Watermarking Techniques
      3. 3 Classification of Watermarking Algorithms
      4. 4 Watermark Embedding, Detection, and Decoding
      5. 5 Copyright Protection Watermarking
      6. 6 Image Content Integrity and Authentication Watermarking
      7. Acknowledgment
    7. Chapter 9.6: Visual Cryptography: The Combinatorial and Halftoning Frameworks
      1. 1 Introduction
      2. 2 Visual Secret Sharing
      3. 3 Visual Steganography
      4. 4 Other Work and Conclusions
  17. SECTION X: Applications of Image Processing
    1. Introduction to Applications of Image Processing
    2. Chapter 10.1: Synthetic Aperture Radar Algorithms
      1. 1 Synthetic Aperture Radar Overview
      2. 2 Image Formation Algorithms
      3. 3 Image Enhancement
      4. 4 Image Exploitation
      5. 5 Chapter Summary
      6. Acknowledgment
    3. Chapter 10.2: Computed Tomography
      1. 1 Introduction
      2. 2 Background
      3. 3 2D Image Reconstruction
      4. 4 Extending 2D Methods into 3D
      5. 5 3D Image Reconstruction
      6. 6 Iterative Reconstruction Methods
      7. 7 Summary
    4. Chapter 10.3: Cardiac Image Processing
      1. 1 Introduction
      2. 2 Coronary Artery Analysis
      3. 3 Analysis of Cardiac Mechanics and Shape
      4. 4 Myocardial Blood Flow (Perfusion)
      5. 5 Electrocardiography
      6. 6 Summary and View of the Future
      7. Acknowledgments
    5. Chapter 10.4: Computer-Aided Detection and Diagnosis in Mammography
      1. 1 Introduction
      2. 2 Computer-Aided Detection of Mammographic Abnormalities
      3. 3 Computer-Aided Diagnosis of Mammographic Abnormalities
      4. 4 Commercial Computer-Aided Detection Systems
      5. 5 Recent Advances and Future Directions in Breast Cancer Computer-Aided Detection/Computer-Aided Diagnosis
      6. Acknowledgments
    6. Chapter 10.5: Fingerprint Classification and Matching
      1. 1 Introduction
      2. 2 Emerging Applications
      3. 3 Fingerprint as a Biometric
      4. 4 History of Fingerprints
      5. 5 System Architecture
      6. 6 Fingerprint Sensing
      7. 7 Fingerprint Representation
      8. 8 Feature Extraction
      9. 9 Fingerprint Enhancement
      10. 10 Fingerprint Classification
      11. 11 Fingerprint Matching
      12. 12 Summary and Future Prospects
    7. Chapter 10.6: Face Recognition from Still Images and Videos
      1. 1 Introduction
      2. 2 Framework of Probabilistic Identity Characterization
      3. 3 Instances of Probabilistic Identity Characterization
      4. 4 Conclusions
      5. Acknowledgment
    8. Chapter 10.7: How Iris Recognition Works
      1. 1 Introduction
      2. 2 Finding an Iris in an Image
      3. 3 Iris Feature Encoding by Two-Dimensional Wavelet Demodulation
      4. 4 The Test of Statistical Independence: Combinatorics of Phase Sequences
      5. 5 Recognizing Irises Regardless of Size, Position, and Orientation
      6. 6 Uniqueness of Failing the Test of Statistical Independence
      7. 7 Decision Environment for Iris Recognition
      8. 8 Speed Performance Summary
      9. 9 Appendix: Two-Dimensional Focus Assessment at the Video Frame Rate
    9. Chapter 10.8: Exploiting Visual Information in Automatic Speech Processing
      1. 1 Introduction
      2. 2 Analysis of Visual Signals
      3. 3 Audiovisual Information Fusion
      4. 4 Audiovisual Automatic Speech Recognition
      5. 5 Audiovisual Speech Synthesis
      6. 6 Audiovisual Speaker Recognition
      7. 7 Summary and Discussion
    10. Chapter 10.9: Confocal Microscopy
      1. 1 Introduction
      2. 2 Image Formation in Confocal Microscopy
      3. 3 Confocal Fluorescence Microscopy
      4. 4 Further Considerations
      5. 5 Types of Confocal Microscopes
      6. 6 Limitations of Confocal Microscopy
      7. 7 Biologic Applications of Confocal Microscopy
      8. 8 Conclusion
    11. Chapter 10.10: Computer-Assisted Microscopy
      1. 1 Introduction
      2. 2 Computer-Assisted Microscopy Systems
      3. 3 Software for Hardware Control
      4. 4 Image Processing and Analysis Software
      5. 5 The Advanced Digital Imaging Research Computerized Microscopy System
      6. 6 Applications in Clinical Cytogenetics
      7. 7 Conclusions
      8. Acknowledgments
    12. Chapter 10.11: Statistical Models of Targets and Clutter for Use in Bayesian Object Recognition
      1. 1 Introduction
      2. 2 Statistical Models
      3. 3 Bayesian Framework
      4. 4 Pose Location Estimation and Performance
      5. 5 Target Recognition and Performance
      6. 6 Discussion
      7. 7 Acknowledgment
  18. Index