Intelligent Image and Video Compression

Communicating Pictures

2nd Edition - April 7, 2021
Authors: David Bull, Fan Zhang
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 0 3 5 3 - 8
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 0 3 5 4 - 5

Intelligent Image and Video Compression: Communicating Pictures, Second Edition explains the requirements, analysis, design and application of a modern video coding system. I… Read more

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Intelligent Image and Video Compression: Communicating Pictures, Second Edition explains the requirements, analysis, design and application of a modern video coding system. It draws on the authors’ extensive academic and professional experience in this field to deliver a text that is algorithmically rigorous yet accessible, relevant to modern standards and practical. It builds on a thorough grounding in mathematical foundations and visual perception to demonstrate how modern image and video compression methods can be designed to meet the rate-quality performance levels demanded by today's applications and users, in the context of prevailing network constraints.

"David Bull and Fan Zhang have written a timely and accessible book on the topic of image and video compression. Compression of visual signals is one of the great technological achievements of modern times, and has made possible the great successes of streaming and social media and digital cinema. Their book, Intelligent Image and Video Compression covers all the salient topics ranging over visual perception, information theory, bandpass transform theory, motion estimation and prediction, lossy and lossless compression, and of course the compression standards from MPEG (ranging from H.261 through the most modern H.266, or VVC) and the open standards VP9 and AV-1. The book is replete with clear explanations and figures, including color where appropriate, making it quite accessible and valuable to the advanced student as well as the expert practitioner. The book offers an excellent glossary and as a bonus, a set of tutorial problems. Highly recommended!” --Al Bovik

Cover image
Title page
Table of Contents
Copyright
List of figures
List of tables
List of algorithms
About the authors
Preface
Chapter 1: Introduction
Abstract
1.1. Communicating pictures: the need for compression
1.2. Applications and drivers
1.3. Requirements and trade-offs in a compression system
1.4. The basics of compression
1.5. The need for standards
1.6. The creative continuum: an interdisciplinary approach
1.7. Summary
References
Chapter 2: The human visual system
Abstract
2.1. Principles and theories of human vision
2.2. Acquisition: the human eye
2.3. The visual cortex
2.4. Visual fields and acuity
2.5. Color processing
2.6. Spatial processing
2.7. Perception of scale and depth
2.8. Temporal and spatio-temporal response
2.9. Attention and eye movements
2.10. Visual masking
2.11. A perceptual basis for image and video compression
References
Chapter 3: Signal processing and information theory fundamentals
Abstract
3.1. Signal and picture sampling
3.2. Statistics of images
3.3. Filtering and transforms
3.4. Quantization
3.5. Linear prediction
3.6. Information and entropy
3.7. Machine learning
3.8. Summary
References
Chapter 4: Digital picture formats and representations
Abstract
4.1. Pixels, blocks, and pictures
4.2. Formats and aspect ratios
4.3. Picture scanning
4.4. Gamma correction
4.5. Color spaces and color transformations
4.6. Measuring and comparing picture quality
4.7. Rates and distortions
4.8. Summary
References
Chapter 5: Transforms for image and video coding
Abstract
5.1. The principles of decorrelating transforms
5.2. Unitary transforms
5.3. Basic transforms
5.4. Optimal transforms
5.5. Discrete cosine transform (DCT)
5.6. Quantization of DCT coefficients
5.7. Performance comparisons
5.8. DCT implementation
5.9. JPEG
5.10. Summary
References
Chapter 6: Filter-banks and wavelet compression
Abstract
6.1. Introduction to multiscale processing
6.2. Perfect reconstruction filter-banks
6.3. Multirate filtering
6.4. Useful filters and filter-banks
6.5. Coefficient quantization and bit allocation
6.6. JPEG2000
6.7. Summary
References
Chapter 7: Lossless compression methods
Abstract
7.1. Motivation for lossless image compression
7.2. Symbol encoding
7.3. Huffman coding
7.4. Symbol formation and encoding
7.5. Golomb coding
7.6. Arithmetic coding
7.7. Performance comparisons
7.8. Summary
References
Chapter 8: Coding moving pictures: motion prediction
Abstract
8.1. Temporal correlation and exploiting temporal redundancy
8.2. Motion models and motion estimation
8.3. Block matching motion estimation (BMME)
8.4. Reduced-complexity motion estimation
8.5. Skip and merge modes
8.6. Motion vector coding
8.7. Summary
References
Chapter 9: The block-based hybrid video codec
Abstract
9.1. The block-based hybrid model for video compression
9.2. Intraframe prediction
9.3. Subpixel motion estimation
9.4. Multiple-reference frame motion estimation
9.5. Variable block sizes for motion estimation
9.6. Variable-sized transforms
9.7. In-loop deblocking operations
9.8. Summary
References
Chapter 10: Measuring and managing picture quality
Abstract
10.1. General considerations and influences
10.2. Subjective testing
10.3. Test datasets and how to use them
10.4. Objective quality metrics
10.5. Rate-distortion optimization
10.6. Rate control
10.7. Summary
References
Chapter 11: Communicating pictures: delivery across networks
Abstract
11.1. The operating environment
11.2. The effects of loss
11.3. Mitigating the effect of bitstream errors
11.4. Transport layer solutions
11.5. Application layer solutions
11.6. Cross-layer solutions
11.7. Inherently robust coding strategies
11.8. Error concealment
11.9. Congestion management
11.10. Summary
References
Chapter 12: Video coding standards and formats
Abstract
12.1. The need for and role of standards
12.2. H.120
12.3. H.261
12.4. MPEG-2/DVB
12.5. H.263
12.6. MPEG-4
12.7. H.264/AVC
12.8. H.265/HEVC
12.9. H.266/VVC
12.10. The alliance for open media (AOM)
12.11. Other standardized and proprietary codecs
12.12. Codec comparisons
12.13. Summary
References
Chapter 13: Communicating pictures – the future
Abstract
13.1. The motivation: more immersive experiences
13.2. New formats and extended video parameter spaces
13.3. Intelligent video compression
13.4. Deep video compression
13.5. Summary
References
Appendix A: Glossary of terms
Appendix B: Tutorial problems
Chapter 1: Introduction
Chapter 2: The human visual system
Chapter 3: Signal processing and information theory fundamentals
Chapter 4: Digital picture formats and representations
Chapter 5: Transforms for image and video coding
Chapter 6: Filter-banks and wavelet compression
Chapter 7: Lossless compression methods
Chapter 8: Coding moving pictures: motion prediction
Chapter 9: The block-based hybrid video codec
Chapter 10: Measuring and managing picture quality
Chapter 11: Communicating pictures: delivery across networks
Chapter 12: Video coding standards and formats
Chapter 13: Communicating pictures – the future
Index

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, UK

Fan Zhang

Dr. Fan (Aaron) Zhang PhD received the B.Sc. (Hons) and M.Sc. degrees from Shanghai Jiao Tong University (2005 and 2008 respectively), and his Ph.D from the University of Bristol (2012). He is currently a Research Fellow in the Visual Information Laboratory at the University of Bristol, working on video compression and immersive video processing. His research interests include perceptual video compression, video quality assessment and immersive video formats. Aaron has published over 30 academic papers and has contributed to two books previous books on video compression. His work on super-resolution-based video compression, has contributed to international standardization processes and he was a co-winner of the 2017 IEEE Grand Challenge on Video Compression.