Academic Press Library in Signal Processing - 1st Edition - ISBN: 9780123965011, 9780123972255

Academic Press Library in Signal Processing, Volume 4

1st Edition

Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing

Editor-in-Chiefs: Sergios Theodoridis Rama Chellappa
eBook ISBN: 9780123972255
Hardcover ISBN: 9780123965011
Imprint: Academic Press
Published Date: 5th September 2013
Page Count: 1088
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Table of Contents

Introduction

Signal Processing at Your Fingertips!

About the Editors

Section Editors

Section 1

Section 2

Section 3

Section 4

Sections 5, 6 and 7

Authors Biography

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

Chapter 10

Chapter 11

Chapter 12

Chapter 14

Chapter 15

Chapter 16

Chapter 17

Chapter 18

Chapter 19

Chapter 20

Chapter 21

Chapter 23

Chapter 24

Chapter 25

Chapter 27

Chapter 28

Chapter 30

Chapter 32

Chapter 34

Chapter 35

Section 1: Image Enhancement/Restoration And Digital Imaging

Chapter 1. Digital Imaging: Capture, Display, Restoration, and Enhancement

Abstract

4.01.1 Introduction

4.01.2 Image capture

4.01.3 Image displays

4.01.4 Restoration

Chapter 2. Image Quality in Consumer Digital Cameras

Abstract

Nomenclature

4.02.1 Introduction

4.02.2 Digital camera image processing chain

4.02.3 Camera engineering

4.02.4 Quality modeling

4.02.5 System interactions

4.02.6 Processing methods and algorithms

4.02.7 Applications

4.02.8 Open issues and future directions

4.02.9 Implementations

4.02.10 Datasets

Glossary

References

Chapter 3. Image and Document Capture—State-of-the-Art and a Glance into the Future

4.03.1 Introduction

4.03.2 Basic steps of conventional document capture processing

4.03.3 Document and image capture applications that are still challenging today

4.03.4 Looking into the future of document and image capture

4.03.5 Data capture via novel sensor multiplexing techniques

4.03.6 Data sets and open source code

4.03.7 Conclusions and future trends

References

Chapter 4. Image Display—Mobile Imaging and Interactive Image Processing

Abstract

4.04.1 The small screen challenge in mobile imaging

4.04.2 Subpixel-based hardware design in mobile display

4.04.3 Subpixel-based software design in mobile display: font rendering

4.04.4 Subpixel-based software design in mobile display: color image down-sampling

4.04.5 Conclusion

References

Chapter 5. Image Display—Printing (Desktop, Commercial)

Abstract

4.05.1 Introduction

4.05.2 Printing technologies

4.05.3 Workflow

4.05.4 Printer models

4.05.5 Research directions in printing

Glossary

References

Chapter 6. Image Restoration: Fundamentals of Image Restoration

Abstract

4.06.1 Introduction

4.06.2 Observation model

4.06.3 Restoration algorithms

4.06.4 Boundary effects

4.06.5 Blur identification

4.06.6 Conclusion

Glossary

References

Chapter 7. Iterative Methods for Image Restoration

Abstract

Acknowledgments

4.07.1 Introduction

4.07.2 Background

4.07.3 Model problems

4.07.4 Iterative methods for unconstrained problems

4.07.5 Iterative methods with nonnegativity constraints

4.07.6 Examples

4.07.7 Concluding remarks and open questions

References

Chapter 8. Image Processing at Your Fingertips: The New Horizon of Mobile Imaging

Abstract

4.08.1 Historical background and overview

4.08.2 Mobile imaging: following Feynman’s idea on infinitesimal machinery

4.08.3 Mobile computing: interacting with computer without an interface

4.08.4 Image processing at fingertips: where mobile imaging meets mobile computing

4.08.5 Applications

4.08.6 Open issues and problems

A. Appendix: course material, source codes and datasets

Supplementary data

Supplementary data

References

Section 2: Image Analysis And Recognition

Chapter 9. Image Analysis and Recognition

4.09.1 General background

4.09.2 Chapter introductions

References

Chapter 10. Multi-Path Marginal Space Learning for Object Detection

Abstract

4.10.1 Introduction

4.10.2 Related work

4.10.3 Marginal Space Learning overview

4.10.4 Face detection with Marginal Space Learning

4.10.5 Multiple computational paths in Marginal Space Learning

4.10.6 Experimental validation

4.10.7 Applications

4.10.8 Open issues and problems

4.10.9 Datasets

4.10.10 Conclusions and future trends

Glossary

References

Chapter 11. Markov Models and MCMC Algorithms in Image Processing

Abstract

4.11.1 Introduction: the probabilistic approach in image analysis

4.11.2 Lattice based models and the Bayesian paradigm

4.11.3 Some inverse problems

4.11.4 Spatial point processes

4.11.5 Multiple objects detection

4.11.6 Conclusion

References

Chapter 12. Identifying Multivariate Imaging Patterns: Supervised, Semi-Supervised, and Unsupervised Learning Perspectives

Abstract

Acknowledgment

4.12.1 Introduction

4.12.2 Materials

4.12.3 Supervised learning of predictive models

4.12.4 Semi-supervised learning of predictive models

4.12.5 Unsupervised learning as the means to disentangle heterogeneity

4.12.6 Summary

References

Section 3: Video Processing

Chapter 13. Video Processing—An Overview

4.13.1 Basic tasks in video analysis

4.13.2 Applications in video analysis

4.13.3 Overview of chapters

Chapter 14. Foveated Image and Video Processing and Search

Abstract

Nomenclature

4.14.1 Introduction

4.14.2 The human visual system

4.14.3 Modeling the human visual system

4.14.4 Foveated images and video

4.14.5 Fixation selection

4.14.6 Applications

4.14.7 Open issues and problems

4.14.8 Implementation/code

4.14.9 Data sets

4.14.10 Conclusions and future trends

Glossary

References

Chapter 15. Segmentation-Free Biometric Recognition Using Correlation Filters

Abstract

4.15.1 Introduction

4.15.2 Advanced correlation filters

4.15.3 Pre- and post-processing images

4.15.4 Correlation filters for videos

4.15.5 Experiments: recognizing subjects in video only using ocular regions

4.15.6 Conclusion

A Appendix

References

Chapter 16. Dynamical Systems in Video Analysis

Abstract

4.16.1 Introduction

4.16.2 Model

4.16.3 Identification

4.16.4 Comparing dynamical models

4.16.5 Applications

4.16.6 Datasets

4.16.7 Discussion

References

Chapter 17. Image-Based Rendering

Abstract

4.17.1 Introduction

4.17.2 Integral imaging

4.17.3 Sampling

4.17.4 Scene representation

4.17.5 Rendering

4.17.6 Applications

4.17.7 Open issues and problems

4.17.8 Implementation/code

4.17.9 Data sets

4.17.10 Conclusions and future trends

Glossary

References

Activity Retrieval in Large Surveillance Videos

Abstract

4.18.1 Introduction

4.18.2 Feature extraction

4.18.3 Indexing

4.18.4 Search engine

4.18.5 Experimental results

4.18.6 Conclusion

References

Chapter 19. Multi-Target Tracking in Video

Abstract

4.19.1 Introduction

4.19.2 Problem formulation

4.19.3 Challenges

4.19.4 Feature extraction

4.19.5 Prediction

4.19.6 Localization and association

4.19.7 Track initialization and termination

4.19.8 Scene contextual information

4.19.9 Summary and outlook

References

Chapter 20. Compressive Sensing for Video Applications

Abstract

Acknowledgments

4.20.1 Introduction

4.20.2 Imaging architectures

4.20.3 Signal models and algorithms

4.20.4 Existing systems for video compressive sensing

4.20.5 Discussion

References

Chapter 21. Virtual Vision for Camera Networks Research

Abstract

Acknowledgments

4.21.1 Introduction

4.21.2 Related work

4.21.3 Virtual vision simulators

4.21.4 Prototype camera networks

4.21.5 Conclusion

Glossary

References

Section 4: Hardware And Software

Chapter 22. Introduction: Hardware and Software

4.22.1 Hardware and software systems

4.22.2 New developments: 3D integration

Chapter 23. Distributed Smart Cameras for Distributed Computer Vision

Abstract

Acknowledgment

4.23.1 Introduction

4.23.2 Basic techniques in computer vision

4.23.3 Camera calibration

4.23.4 Gesture recognition

4.23.5 Tracking with overlapping fields-of-view

4.23.6 Tracking in sparse camera networks

4.23.7 Summary

References

Chapter 24. Mapping Parameterized Dataflow Graphs onto FPGA Platforms

Abstract

4.24.1 Introduction

4.24.2 Background

4.24.3 Dynamic reconfiguration techniques in FPGAs

4.24.4 Modeling dynamic reconfiguration using PSDF techniques

4.24.5 Hardware mapping

4.24.6 Case studies

4.24.7 Conclusion

References

Distributed Estimation

Abstract

4.25.1 Notation

4.25.2 Network with a star topology

4.25.3 Non-ideal networks with star topology

4.25.4 Network with arbitrary topology

4.25.5 Computational complexity and communication cost

4.25.6 Conclusion

Appendix

References

Section 5: Audio Signal Processing

Chapter 26. Introduction to Audio Signal Processing

4.26.1 Background

4.26.2 Overview of the chapters

Chapter 27. Music Signal Processing

Abstract

4.27.1 Introduction

4.27.2 Pitch and harmony

4.27.3 Tempo and beat

4.27.4 Timbre and instrumentation

4.27.5 Melody and vocals

References

Chapter 28. Perceptual Audio Coding

Abstract

Introduction

4.28.1 Principles and background

4.28.2 Concepts and architectures

4.28.3 Standards

4.28.4 Summary and conclusions

References

Section 6: Acoustic Signal Processing

Chapter 29. Introduction to Acoustic Signal Processing

4.29.1 Background

4.29.2 Overview of the chapters

Chapter 30. Acoustic Echo Control

Abstract

Nomenclature

List of Abbreviations

4.30.1 Introduction

4.30.2 Echo cancellation and postfiltering

4.30.3 Echo suppression

4.30.4 Multichannel acoustic echo cancellation

4.30.5 Nonlinear modeling and cancellation of echo

4.30.6 Application to realistic and real systems

4.30.7 Links to codes and recommendations

4.30.8 Conclusions, open issues, future trends

Glossary

References

Chapter 31. Dereverberation

Abstract

Acknowledgments

4.31.1 Introduction and overview

4.31.2 Example applications

4.31.3 Room reverberation

4.31.4 Measurement of reverberation

4.31.5 Spatial filtering for dereverberation

4.31.6 Speech enhancement methods for dereverberation

4.31.7 Acoustic channel-based methods for dereverberation

4.31.8 Summary and conclusions

List of Abbreviations

References

Chapter 32. Sound Field Synthesis

Abstract

Acknowledgments

4.32.1 Introduction

4.32.2 Acoustic wave equation

4.32.3 Signal representations

4.32.4 Response to sound sources

4.32.5 Physical foundations of sound field synthesis

4.32.6 Near-field Compensated Higher Order Ambisonics (NFC-HOA)

4.32.7 Spectral division method (SDM)

4.32.8 Wave Field Synthesis (WFS)

4.32.9 Supplementary data

4.32.10 Supplementary data

References

Section 7: Speech Processing

Chapter 33. Introduction to Speech Processing

4.33.1 Background

4.33.2 Overview of the chapters

Chapter 34. Speech Production Modeling and Analysis

Abstract

4.34.1 Introduction

4.34.2 Speech production modeling

4.34.3 Estimating the voice source signal

4.34.4 Glottal closure instants

4.34.5 Voice source modeling

References

Chapter 35. Enhancement

Abstract

4.35.1 Introduction

4.35.2 Speech enhancement methods

4.35.3 Enabling algorithms

4.35.4 Intelligibility and quality measures

List of Abbreviations

References

Index


Description

This fourth volume, 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

Key Features

  • 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

Readership

PhD students

Post Docs

R&D engineers in signal processing and wireless and mobile communications

Consultants


Details

No. of pages:
1088
Language:
English
Copyright:
© Academic Press 2014
Published:
Imprint:
Academic Press
eBook ISBN:
9780123972255
Hardcover ISBN:
9780123965011

About the Editor-in-Chiefs

Sergios Theodoridis Editor-in-Chief

Sergios Theodoridis acquired a Physics degree with honors from the University of Athens, Greece in 1973 and a MSc and a Ph.D. degree in Signal Processing and Communications from the University of Birmingham, UK in 1975 and 1978 respectively. Since 1995 he has been a Professor with the Department of Informatics and Communications at the University of Athens.

Affiliations and Expertise

Department of Informatics and Telecommunications, University of Athens, Greece

Rama Chellappa Editor-in-Chief

Prof. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from Indian Institute of Science, Bangalore, in 1977. He received M.S.E.E. and Ph.D. Degrees in Electrical Engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981-1986) and Associate Professor (1986-1991) and Director of the Signal and Image Processing Institute (1988-1990) at University of Southern California, Los Angeles. Over the last 29 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has co-authored and edited books on MRFs, face and gait recognition and collected works on image processing and analysis. His current research interests are face and gait analysis, markerless motion capture, 3D modeling from video, image and video-based recognition and exploitation and hyper spectral processing.

Affiliations and Expertise

University of Maryland, College Park, USA