Academic Press Library in Signal Processing
Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing
- 1st Edition, Volume 4 - October 7, 2013
- Latest edition
- Editors: Sergios Theodoridis, Rama Chellappa
- Language: English
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 te… Read more
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
- 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
PhD students
Post Docs
R&D engineers in signal processing and wireless and mobile communications
Consultants
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
- Edition: 1
- Latest edition
- Volume: 4
- Published: October 7, 2013
- Language: English
ST
Sergios Theodoridis
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, GreeceRC
Rama Chellappa
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, USARead Academic Press Library in Signal Processing on ScienceDirect