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Digital Video Processing, Second Edition

Book Description

This is the Rough Cut version of the printed book.

In the nearly twenty years since the first edition of Digital Video Processing, digital video has become ubiquitous, and the most successful techniques and algorithms for different video processing tasks have become more clear. Digital Video Processing, Second Edition, significantly improves the organization of the material and the presentation style in a truly tutorial manner and updates the technical content with the most recent knowledge of techniques, successful algorithms, and up-to-date information in order to once again position the book as necessary to your library.

This is a unique, comprehensive textbook, written by a single author in tutorial style. It covers fundamentals of digital image and video processing with equal emphasis on image filtering, motion estimation, video segmentation, video filtering, and image/video compression. After reading the book, the reader will

  • understand theoretical foundations of image and video processing methods

  • learn the most popular and successful techniques to solve common image and video processing problems

  • reinforce their understanding by solving problems and doing MATLAB projects at the end of each chapter

  • Table of Contents

    1. Title Page
    2. Copyright Page
    3. Dedication
    4. Contents
    5. Preface
    6. About the Author
    7. Chapter 1. Multidimensional Signals and Systems
      1. 1.1. Multidimensional Signals
      2. 1.2. Multidimensional Transforms
      3. 1.3. Multidimensional Systems
      4. 1.4. Multidimensional Sampling Theory
      5. 1.5. Sampling Structure Conversion
      6. References
      7. Exercises
      8. MATLAB Exercises
    8. Chapter 2. Digital Images and Video
      1. 2.1. Human Visual System and Color
      2. 2.2. Analog Video
      3. 2.3. Digital Video
      4. 2.4. 3D Video
      5. 2.5. Digital Video Applications
      6. 2.6. Image and Video Quality
      7. References
    9. Chapter 3. Image Filtering
      1. 3.1. Image Smoothing
      2. 3.2. Image Resampling and Multiresolution Representations
      3. 3.3. Image Gradient Estimation, Edge and Feature Detection
      4. 3.4. Image Enhancement
      5. 3.5. Image Denoising
      6. 3.6. Image Restoration
      7. References
      8. Exercises
      9. MATLAB Exercises
      10. MATLAB Resources
    10. Chapter 4. Motion Estimation
      1. 4.1. Image Formation
      2. 4.2. Motion Models
      3. 4.3. 2D Apparent Motion Estimation
      4. 4.4. Differential Methods
      5. 4.5. Matching Methods
      6. 4.6. Non-linear Optimization Methods
      7. 4.7. Transform Domain Methods
      8. 4.8. 3D Motion and Structure Estimation
      9. References
      10. Exercises
      11. MATLAB Exercises
      12. MATLAB Resources
    11. Chapter 5. Video Segmentation and Tracking
      1. 5.1. Image Segmentation
      2. 5.2. Change Detection
      3. 5.3. Motion Segmentation
      4. 5.4. Motion Tracking
      5. 5.5. Image and Video Matting
      6. 5.6. Performance Evaluation
      7. References
      8. MATLAB Exercises
      9. Internet Resources
    12. Chapter 6. Video Filtering
      1. 6.1. Theory of Spatio-Temporal Filtering
      2. 6.2. Video Format Conversion
      3. 6.3. Multi-Frame Noise Filtering
      4. 6.4. Multi-Frame Restoration
      5. 6.5. Multi-Frame Super-resolution
      6. References
      7. Exercises
      8. MATLAB Exercises
    13. Chapter 7. Image Compression
      1. 7.1. Basics of Image Compression
      2. 7.2. Lossless Image Compression
      3. 7.3. Discrete Cosine Transform Coding and JPEG
      4. 7.4. Wavelet Transform Coding and JPEG2000
      5. References
      6. Exercises
      7. Internet Resources
    14. Chapter 8. Video Compression
      1. 8.1. Video Compression Approaches
      2. 8.2. Early Video Compression Standards
      3. 8.3. MPEG-4 AVC/ITU-T H.264 Standard
      4. 8.4. High Efficiency Video Coding (HEVC) Standard
      5. 8.5. Scalable Video Compression
      6. 8.6. Stereo and Multi-View Video Compression
      7. References
      8. Exercises
      9. Internet Resources
    15. Appendix A. Vector-Matrix Operations in Image and Video Processing
      1. A.1. Two-Dimensional Convolution
      2. A.2. Two-Dimensional Discrete Fourier Transform
      3. A.3. Three-Dimensional Rotation – Rotation Matrix
      4. References
      5. Exercises
    16. Appendix B. Ill-Posed Problems in Image and Video Processing
      1. B.1. Image Representations
      2. B.2. Overview of Image Models
      3. B.3. Basics of Sparse Image Modeling
      4. B.4. Well-Posed Formulations of Ill-Posed Problems
      5. References
    17. Appendix C. Markov and Gibbs Random Fields
      1. C.1. Equivalence of Markov Random Fields and Gibbs Random Fields
      2. C.2. Gibbs Distribution as an a priori PDF Model
      3. C.3. Computation of Local Conditional Probabilities from a Gibbs Distribution
      4. References
    18. Appendix D. Optimization Methods
      1. D.1. Gradient-Based Optimization
      2. D.2. Simulated Annealing
      3. D.3. Greedy Methods
      4. References
    19. Appendix E. Model Fitting
      1. E.1. Least Squares Fitting
      2. E.2. Least Squares Solution of Homogeneous Linear Equations
      3. E.3. Total Least Squares Fitting
      4. E.4. Random Sample Consensus (RANSAC)
      5. References