Academic Press Library in Signal Processing
Image and Video Compression and Multimedia
- 1st Edition, Volume 5 - July 24, 2014
- Editors: David Bull, Sergios Theodoridis, Min Wu, Rama Chellappa
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 4 2 0 1 4 9 - 1
- eBook ISBN:9 7 8 - 0 - 1 2 - 4 2 0 1 5 7 - 6
This fifth 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 fifth 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 and video compression and multimedia.
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 and Video Compression and Multimedia
- 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
Electrical/electronic engineers, signal processing and communications engineering. University researchers and R&D engineers in industry
- Introduction
- Signal Processing at Your Fingertips!
- About the Editors
- Section Editors
- Authors Biography
- Section 1: Image/Video Compression
- Chapter 1. An Introduction to Video Coding
- Abstract
- Nomenclature
- 5.01.1 Introduction
- 5.01.2 Applications areas for video coding
- 5.01.3 Requirements of a compression system
- 5.01.4 The basics of compression
- 5.01.5 Decorrelating transforms
- 5.01.6 Symbol encoding
- 5.01.7 Motion estimation
- 5.01.8 The block-based motion-compensated video coding architecture
- 5.01.9 Standardization of video coding systems
- 5.01.10 Conclusions
- Additional resources
- Glossary of terms
- References
- Chapter 2. Motion Estimation—A Video Coding Viewpoint
- Abstract
- Nomenclature
- 5.02.1 Introduction
- 5.02.2 Motion representation and models
- 5.02.3 Optical flow approaches
- 5.02.4 Pel-recursive approaches
- 5.02.5 Transform-domain approaches
- 5.02.6 Block matching approaches
- 5.02.7 Parametric motion estimation
- 5.02.8 Multi-resolution approaches
- 5.02.9 Motion compensation
- 5.02.10 Performance assessment criteria for motion estimation algorithms
- 5.02.11 Summary and concluding remarks
- Relevant websites
- Glossary
- References
- Chapter 3. High Efficiency Video Coding (HEVC) for Next Generation Video Applications
- Abstract
- Nomenclature
- 5.03.1 Introduction
- 5.03.2 Requirements and solutions for video compression
- 5.03.3 Basic principles behind HEVC
- 5.03.4 Performance evaluation
- 5.03.5 Conclusions
- Relevant Websites
- Glossary
- References
- Chapter 4. Stereoscopic and Multi-View Video Coding
- Abstract
- Nomenclature
- 5.04.1 Introduction
- 5.04.2 Fundamentals of stereoscopic vision
- 5.04.3 3D display technologies
- 5.04.4 Applications of stereoscopic and multi-view video
- 5.04.5 Compression of stereoscopic and multi-view video
- 5.04.6 Quality evaluation of 3D video
- 5.04.7 Conclusions
- Relevant Websites
- References
- Chapter 5. Perceptually Optimized Video Compression
- Abstract
- Nomenclature
- 5.05.1 Introduction
- 5.05.2 Perceptual coding tools in video coding architectures
- 5.05.3 The modeling of the human visual system sensitivity to coding artifacts
- 5.05.4 Integration of JND models in video coding architectures
- 5.05.5 Practical perceptual video coding schemes
- 5.05.6 Conclusions and considerations for future research directions
- Glossary
- References
- Chapter 6. How to Use Texture Analysis and Synthesis Methods for Video Compression
- Abstract
- Nomenclature
- 5.06.1 Introduction
- 5.06.2 Perception-oriented video coding strategies
- 5.06.3 Block-based video coding techniques
- 5.06.4 Region-based video coding techniques
- 5.06.5 Conclusion
- Relevant websites of open source software
- Glossary
- References
- Chapter 7. Measuring Video Quality
- Abstract
- Nomenclature
- 5.07.1 Introduction
- 5.07.2 Background
- 5.07.3 Subjective testing
- 5.07.4 Subjective datasets
- 5.07.5 Objective quality metrics
- 5.07.6 Conclusions
- Additional resources
- References
- Chapter 8. Multiple Description Coding
- Abstract
- Nomenclature
- 5.08.1 Introduction and history
- 5.08.2 Theoretical basis
- 5.08.3 Speech coding
- 5.08.4 Image coding
- 5.08.5 Video coding
- 5.08.6 Network coding
- 5.08.7 Stereoscopic 3D
- 5.08.8 Other applications
- 5.08.9 Implementations and patents
- 5.08.10 Conclusion
- List of Relevant Websites
- References
- Chapter 9. Video Error Concealment
- Abstract
- Nomenclature
- 5.09.1 Introduction
- 5.09.2 Spatial error concealment (SEC)
- 5.09.3 Temporal error concealment (TEC)
- 5.09.4 Mode selection
- 5.09.5 Discussion and conclusions
- Glossary
- References
- Chapter 1. An Introduction to Video Coding
- Section 2: Multimedia Signal Processing
- Chapter 10. Introduction to Multimedia Signal Processing
- References
- Chapter 11. Multimedia Streaming
- Abstract
- Overview
- 5.11.1 Introduction
- 5.11.2 Transport protocols
- 5.11.3 Streaming on wired networks
- 5.11.4 Streaming on wireless networks
- 5.11.5 Error control, detection, concealment
- 5.11.6 Scalable video coding
- 5.11.7 Multiple Description Coding
- 5.11.8 Network coding
- Conclusions
- Glossary
- References
- Chapter 12. Multimedia Content-Based Visual Retrieval
- Abstract
- 5.12.1 Introduction
- 5.12.2 General pipeline overview
- 5.12.3 Local feature representation
- 5.12.4 Feature quantization
- 5.12.5 Index strategy
- 5.12.6 Retrieval scoring
- 5.12.7 Post-processing
- 5.12.8 Conclusion
- Acknowledgment
- References
- Chapter 13. Joint Audio-Visual Processing for Video Copy Detection
- Abstract
- 5.13.1 Introduction
- 5.13.2 Visual-based video copy detection algorithm
- 5.13.3 Audio-based video copy detection
- 5.13.4 Joint audio- and visual-based video copy detection
- 5.13.5 Copy and near-duplicate detection
- 5.13.6 Region and partial content search
- 5.13.7 Conclusion and future trends
- References
- Chapter 10. Introduction to Multimedia Signal Processing
- Index
- Edition: 1
- Volume: 5
- Published: July 24, 2014
- Language: English
DB
David Bull
Professor David R. Bull PhD, FIET, FIEEE, CEng. obtained his PhD from the University of Cardiff in 1988. He currently holds the Chair in Signal Processing at the University of Bristol where he is head of the Visual Information Laboratory and Director of Bristol Vision Institute, a group of some 150 researchers in vision science, spanning engineering, psychology, biology, medicine and the creative arts. In 1996 David helped to establish the UK DTI Virtual Centre of Excellence in Digital Broadcasting and Multimedia Technology and was one of its Directors from 1997-2000. He has also advised Government through membership of the UK Foresight Panel, DSAC and the HEFCE Research Evaluation Framework. He is also now Director of the UK Government’s new MyWorld Strength in Places programme.
David has worked widely across image and video processing focused on streaming, broadcast and wireless applications. He has published over 600 academic papers, various articles and 4 books and has given numerous invited/keynote lectures and tutorials. He has also received awards including the IEE Ambrose Fleming Premium for his work on Primitive Operator Digital Filters and a best Paper Award for his work on Link Adaptation for Video Transmission. David’s work has been exploited commercially and he has acted as a consultant for companies and governments across the globe. In 2001, he co-founded ProVision Communication Technologies Ltd., who launched the world’s first robust multi-source wireless HD sender for consumer use. His recent award-winning and pioneering work on perceptual video compression using deep learning, has produced world-leading rate-quality performance.
Affiliations and expertise
University of Bristol, UKST
Sergios Theodoridis
Sergios Theodoridis is professor emeritus of machine learning and data processing with the National and Kapodistrian University of Athens, Athens, Greece. He has also served as distinguished professor with the Aalborg University Denmark and as professor with the Chinese University of Hong Kong, Shenzhen, China. In 2023, he received an honorary doctorate degree (D.Sc) from the University of Edinburgh, U.K. He has also received a number of prestigious awards, including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the 2017 European Association for Signal Processing (EURASIP) Athanasios Papoulis Award, the 2014 IEEE Signal Processing Society Carl Friedrich Gauss Education Award, and the 2014 EURASIP Meritorious Service Award. He has served as president of EURASIP and vice president for the IEEE Signal Processing Society. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
Affiliations and expertise
Professor of Machine Learning and Signal Processing, National and Kapodistrian University of Athens, 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