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Digital Video Processing, Second Edition

Book Description

Over the years, thousands of engineering students and professionals relied on Digital Video Processing as the definitive, in-depth guide to digital image and video processing technology. Now, Dr. A. Murat Tekalp has completely revamped the first edition to reflect today’s technologies, techniques, algorithms, and trends.

Digital Video Processing, Second Edition, reflects important advances in image processing, computer vision, and video compression, including new applications such as digital cinema, ultra-high-resolution video, and 3D video.

This edition offers rigorous, comprehensive, balanced, and quantitative coverage of image filtering, motion estimation, tracking, segmentation, video filtering, and compression. Now organized and presented as a true tutorial, it contains updated problem sets and new MATLAB projects in every chapter.

Coverage includes

  • Multi-dimensional signals/systems: transforms, sampling, and lattice conversion

  • Digital images and video: human vision, analog/digital video, and video quality

  • Image filtering: gradient estimation, edge detection, scaling, multi-resolution representations, enhancement, de-noising, and restoration

  • Motion estimation: image formation; motion models; differential, matching, optimization, and transform-domain methods; and 3D motion and shape estimation

  • Video segmentation: color and motion segmentation, change detection, shot boundary detection, video matting, video tracking, and performance evaluation

  • Multi-frame filtering: motion-compensated filtering, multi-frame standards conversion, multi-frame noise filtering, restoration, and super-resolution

  • Image compression: lossless compression, JPEG, wavelets, and JPEG2000

  • Video compression: early standards, ITU-T H.264/MPEG-4 AVC, HEVC, Scalable Video Compression, and stereo/multi-view approaches

  • 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