Academic Press Library in Signal Processing

Academic Press Library in Signal Processing

Released September 2013
Publisher(s): Academic Press
ISBN: 9780123972255

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Book description

This fourth volume of a five volume set, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in Image, Video Processing and Analysis, Hardware,  Audio, Acoustic and Speech Processing.

With this reference source you will:

  • Quickly grasp a new area of research 
  • Understand the underlying principles of a topic and its application
  • Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved


  • Quick tutorial reviews of important and emerging topics of research in Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing
  • Presents core principles and shows their application
  • Reference content on core principles, technologies, algorithms and applications
  • Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge
  • Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Introduction
    1. Signal Processing at Your Fingertips!
  6. About the Editors
  7. Section Editors
    1. Section 1
    2. Section 2
    3. Section 3
    4. Section 4
    5. Sections 5, 6 and 7
  8. Authors Biography
    1. Chapter 2
    2. Chapter 3
    3. Chapter 4
    4. Chapter 5
    5. Chapter 6
    6. Chapter 7
    7. Chapter 8
    8. Chapter 10
    9. Chapter 11
    10. Chapter 12
    11. Chapter 14
    12. Chapter 15
    13. Chapter 16
    14. Chapter 17
    15. Chapter 18
    16. Chapter 19
    17. Chapter 20
    18. Chapter 21
    19. Chapter 23
    20. Chapter 24
    21. Chapter 25
    22. Chapter 27
    23. Chapter 28
    24. Chapter 30
    25. Chapter 32
    26. Chapter 34
    27. Chapter 35
  9. Section 1: Image Enhancement/Restoration And Digital Imaging
    1. Chapter 1. Digital Imaging: Capture, Display, Restoration, and Enhancement
      1. Abstract
      2. 4.01.1 Introduction
      3. 4.01.2 Image capture
      4. 4.01.3 Image displays
      5. 4.01.4 Restoration
    2. Chapter 2. Image Quality in Consumer Digital Cameras
      1. Abstract
      2. Nomenclature
      3. 4.02.1 Introduction
      4. 4.02.2 Digital camera image processing chain
      5. 4.02.3 Camera engineering
      6. 4.02.4 Quality modeling
      7. 4.02.5 System interactions
      8. 4.02.6 Processing methods and algorithms
      9. 4.02.7 Applications
      10. 4.02.8 Open issues and future directions
      11. 4.02.9 Implementations
      12. 4.02.10 Datasets
      13. Glossary
      14. References
    3. Chapter 3. Image and Document Capture—State-of-the-Art and a Glance into the Future
      1. 4.03.1 Introduction
      2. 4.03.2 Basic steps of conventional document capture processing
      3. 4.03.3 Document and image capture applications that are still challenging today
      4. 4.03.4 Looking into the future of document and image capture
      5. 4.03.5 Data capture via novel sensor multiplexing techniques
      6. 4.03.6 Data sets and open source code
      7. 4.03.7 Conclusions and future trends
      8. References
    4. Chapter 4. Image Display—Mobile Imaging and Interactive Image Processing
      1. Abstract
      2. 4.04.1 The small screen challenge in mobile imaging
      3. 4.04.2 Subpixel-based hardware design in mobile display
      4. 4.04.3 Subpixel-based software design in mobile display: font rendering
      5. 4.04.4 Subpixel-based software design in mobile display: color image down-sampling
      6. 4.04.5 Conclusion
      7. References
    5. Chapter 5. Image Display—Printing (Desktop, Commercial)
      1. Abstract
      2. 4.05.1 Introduction
      3. 4.05.2 Printing technologies
      4. 4.05.3 Workflow
      5. 4.05.4 Printer models
      6. 4.05.5 Research directions in printing
      7. Glossary
      8. References
    6. Chapter 6. Image Restoration: Fundamentals of Image Restoration
      1. Abstract
      2. 4.06.1 Introduction
      3. 4.06.2 Observation model
      4. 4.06.3 Restoration algorithms
      5. 4.06.4 Boundary effects
      6. 4.06.5 Blur identification
      7. 4.06.6 Conclusion
      8. Glossary
      9. References
    7. Chapter 7. Iterative Methods for Image Restoration
      1. Abstract
      2. Acknowledgments
      3. 4.07.1 Introduction
      4. 4.07.2 Background
      5. 4.07.3 Model problems
      6. 4.07.4 Iterative methods for unconstrained problems
      7. 4.07.5 Iterative methods with nonnegativity constraints
      8. 4.07.6 Examples
      9. 4.07.7 Concluding remarks and open questions
      10. References
    8. Chapter 8. Image Processing at Your Fingertips: The New Horizon of Mobile Imaging
      1. Abstract
      2. 4.08.1 Historical background and overview
      3. 4.08.2 Mobile imaging: following Feynman’s idea on infinitesimal machinery
      4. 4.08.3 Mobile computing: interacting with computer without an interface
      5. 4.08.4 Image processing at fingertips: where mobile imaging meets mobile computing
      6. 4.08.5 Applications
      7. 4.08.6 Open issues and problems
      8. A. Appendix: course material, source codes and datasets
      9. Supplementary data
      10. Supplementary data
      11. References
  10. Section 2: Image Analysis And Recognition
    1. Chapter 9. Image Analysis and Recognition
      1. 4.09.1 General background
      2. 4.09.2 Chapter introductions
      3. References
    2. Chapter 10. Multi-Path Marginal Space Learning for Object Detection
      1. Abstract
      2. 4.10.1 Introduction
      3. 4.10.2 Related work
      4. 4.10.3 Marginal Space Learning overview
      5. 4.10.4 Face detection with Marginal Space Learning
      6. 4.10.5 Multiple computational paths in Marginal Space Learning
      7. 4.10.6 Experimental validation
      8. 4.10.7 Applications
      9. 4.10.8 Open issues and problems
      10. 4.10.9 Datasets
      11. 4.10.10 Conclusions and future trends
      12. Glossary
      13. References
    3. Chapter 11. Markov Models and MCMC Algorithms in Image Processing
      1. Abstract
      2. 4.11.1 Introduction: the probabilistic approach in image analysis
      3. 4.11.2 Lattice based models and the Bayesian paradigm
      4. 4.11.3 Some inverse problems
      5. 4.11.4 Spatial point processes
      6. 4.11.5 Multiple objects detection
      7. 4.11.6 Conclusion
      8. References
    4. Chapter 12. Identifying Multivariate Imaging Patterns: Supervised, Semi-Supervised, and Unsupervised Learning Perspectives
      1. Abstract
      2. Acknowledgment
      3. 4.12.1 Introduction
      4. 4.12.2 Materials
      5. 4.12.3 Supervised learning of predictive models
      6. 4.12.4 Semi-supervised learning of predictive models
      7. 4.12.5 Unsupervised learning as the means to disentangle heterogeneity
      8. 4.12.6 Summary
      9. References
  11. Section 3: Video Processing
    1. Chapter 13. Video Processing—An Overview
      1. 4.13.1 Basic tasks in video analysis
      2. 4.13.2 Applications in video analysis
      3. 4.13.3 Overview of chapters
    2. Chapter 14. Foveated Image and Video Processing and Search
      1. Abstract
      2. Nomenclature
      3. 4.14.1 Introduction
      4. 4.14.2 The human visual system
      5. 4.14.3 Modeling the human visual system
      6. 4.14.4 Foveated images and video
      7. 4.14.5 Fixation selection
      8. 4.14.6 Applications
      9. 4.14.7 Open issues and problems
      10. 4.14.8 Implementation/code
      11. 4.14.9 Data sets
      12. 4.14.10 Conclusions and future trends
      13. Glossary
      14. References
    3. Chapter 15. Segmentation-Free Biometric Recognition Using Correlation Filters
      1. Abstract
      2. 4.15.1 Introduction
      3. 4.15.2 Advanced correlation filters
      4. 4.15.3 Pre- and post-processing images
      5. 4.15.4 Correlation filters for videos
      6. 4.15.5 Experiments: recognizing subjects in video only using ocular regions
      7. 4.15.6 Conclusion
      8. A Appendix
      9. References
    4. Chapter 16. Dynamical Systems in Video Analysis
      1. Abstract
      2. 4.16.1 Introduction
      3. 4.16.2 Model
      4. 4.16.3 Identification
      5. 4.16.4 Comparing dynamical models
      6. 4.16.5 Applications
      7. 4.16.6 Datasets
      8. 4.16.7 Discussion
      9. References
    5. Chapter 17. Image-Based Rendering
      1. Abstract
      2. 4.17.1 Introduction
      3. 4.17.2 Integral imaging
      4. 4.17.3 Sampling
      5. 4.17.4 Scene representation
      6. 4.17.5 Rendering
      7. 4.17.6 Applications
      8. 4.17.7 Open issues and problems
      9. 4.17.8 Implementation/code
      10. 4.17.9 Data sets
      11. 4.17.10 Conclusions and future trends
      12. Glossary
      13. References
    6. Activity Retrieval in Large Surveillance Videos
      1. Abstract
      2. 4.18.1 Introduction
      3. 4.18.2 Feature extraction
      4. 4.18.3 Indexing
      5. 4.18.4 Search engine
      6. 4.18.5 Experimental results
      7. 4.18.6 Conclusion
      8. References
    7. Chapter 19. Multi-Target Tracking in Video
      1. Abstract
      2. 4.19.1 Introduction
      3. 4.19.2 Problem formulation
      4. 4.19.3 Challenges
      5. 4.19.4 Feature extraction
      6. 4.19.5 Prediction
      7. 4.19.6 Localization and association
      8. 4.19.7 Track initialization and termination
      9. 4.19.8 Scene contextual information
      10. 4.19.9 Summary and outlook
      11. References
    8. Chapter 20. Compressive Sensing for Video Applications
      1. Abstract
      2. Acknowledgments
      3. 4.20.1 Introduction
      4. 4.20.2 Imaging architectures
      5. 4.20.3 Signal models and algorithms
      6. 4.20.4 Existing systems for video compressive sensing
      7. 4.20.5 Discussion
      8. References
    9. Chapter 21. Virtual Vision for Camera Networks Research
      1. Abstract
      2. Acknowledgments
      3. 4.21.1 Introduction
      4. 4.21.2 Related work
      5. 4.21.3 Virtual vision simulators
      6. 4.21.4 Prototype camera networks
      7. 4.21.5 Conclusion
      8. Glossary
      9. References
  12. Section 4: Hardware And Software
    1. Chapter 22. Introduction: Hardware and Software
      1. 4.22.1 Hardware and software systems
      2. 4.22.2 New developments: 3D integration
    2. Chapter 23. Distributed Smart Cameras for Distributed Computer Vision
      1. Abstract
      2. Acknowledgment
      3. 4.23.1 Introduction
      4. 4.23.2 Basic techniques in computer vision
      5. 4.23.3 Camera calibration
      6. 4.23.4 Gesture recognition
      7. 4.23.5 Tracking with overlapping fields-of-view
      8. 4.23.6 Tracking in sparse camera networks
      9. 4.23.7 Summary
      10. References
    3. Chapter 24. Mapping Parameterized Dataflow Graphs onto FPGA Platforms
      1. Abstract
      2. 4.24.1 Introduction
      3. 4.24.2 Background
      4. 4.24.3 Dynamic reconfiguration techniques in FPGAs
      5. 4.24.4 Modeling dynamic reconfiguration using PSDF techniques
      6. 4.24.5 Hardware mapping
      7. 4.24.6 Case studies
      8. 4.24.7 Conclusion
      9. References
    4. Distributed Estimation
      1. Abstract
      2. 4.25.1 Notation
      3. 4.25.2 Network with a star topology
      4. 4.25.3 Non-ideal networks with star topology
      5. 4.25.4 Network with arbitrary topology
      6. 4.25.5 Computational complexity and communication cost
      7. 4.25.6 Conclusion
      8. Appendix
      9. References
  13. Section 5: Audio Signal Processing
    1. Chapter 26. Introduction to Audio Signal Processing
      1. 4.26.1 Background
      2. 4.26.2 Overview of the chapters
    2. Chapter 27. Music Signal Processing
      1. Abstract
      2. 4.27.1 Introduction
      3. 4.27.2 Pitch and harmony
      4. 4.27.3 Tempo and beat
      5. 4.27.4 Timbre and instrumentation
      6. 4.27.5 Melody and vocals
      7. References
    3. Chapter 28. Perceptual Audio Coding
      1. Abstract
      2. Introduction
      3. 4.28.1 Principles and background
      4. 4.28.2 Concepts and architectures
      5. 4.28.3 Standards
      6. 4.28.4 Summary and conclusions
      7. References
  14. Section 6: Acoustic Signal Processing
    1. Chapter 29. Introduction to Acoustic Signal Processing
      1. 4.29.1 Background
      2. 4.29.2 Overview of the chapters
    2. Chapter 30. Acoustic Echo Control
      1. Abstract
      2. Nomenclature
      3. List of Abbreviations
      4. 4.30.1 Introduction
      5. 4.30.2 Echo cancellation and postfiltering
      6. 4.30.3 Echo suppression
      7. 4.30.4 Multichannel acoustic echo cancellation
      8. 4.30.5 Nonlinear modeling and cancellation of echo
      9. 4.30.6 Application to realistic and real systems
      10. 4.30.7 Links to codes and recommendations
      11. 4.30.8 Conclusions, open issues, future trends
      12. Glossary
      13. References
    3. Chapter 31. Dereverberation
      1. Abstract
      2. Acknowledgments
      3. 4.31.1 Introduction and overview
      4. 4.31.2 Example applications
      5. 4.31.3 Room reverberation
      6. 4.31.4 Measurement of reverberation
      7. 4.31.5 Spatial filtering for dereverberation
      8. 4.31.6 Speech enhancement methods for dereverberation
      9. 4.31.7 Acoustic channel-based methods for dereverberation
      10. 4.31.8 Summary and conclusions
      11. List of Abbreviations
      12. References
    4. Chapter 32. Sound Field Synthesis
      1. Abstract
      2. Acknowledgments
      3. 4.32.1 Introduction
      4. 4.32.2 Acoustic wave equation
      5. 4.32.3 Signal representations
      6. 4.32.4 Response to sound sources
      7. 4.32.5 Physical foundations of sound field synthesis
      8. 4.32.6 Near-field Compensated Higher Order Ambisonics (NFC-HOA)
      9. 4.32.7 Spectral division method (SDM)
      10. 4.32.8 Wave Field Synthesis (WFS)
      11. 4.32.9 Supplementary data
      12. 4.32.10 Supplementary data
      13. References
  15. Section 7: Speech Processing
    1. Chapter 33. Introduction to Speech Processing
      1. 4.33.1 Background
      2. 4.33.2 Overview of the chapters
    2. Chapter 34. Speech Production Modeling and Analysis
      1. Abstract
      2. 4.34.1 Introduction
      3. 4.34.2 Speech production modeling
      4. 4.34.3 Estimating the voice source signal
      5. 4.34.4 Glottal closure instants
      6. 4.34.5 Voice source modeling
      7. References
    3. Chapter 35. Enhancement
      1. Abstract
      2. 4.35.1 Introduction
      3. 4.35.2 Speech enhancement methods
      4. 4.35.3 Enabling algorithms
      5. 4.35.4 Intelligibility and quality measures
      6. List of Abbreviations
      7. References
  16. Index

Product information

  • Title: Academic Press Library in Signal Processing
  • Author(s):
  • Release date: September 2013
  • Publisher(s): Academic Press
  • ISBN: 9780123972255