Intelligent Image and Video Compression: Communicating Pictures

Author:   David Bull (University of Bristol, UK) ,  Fan Zhang (School of Astronautics, Northwestern Polytechnical University, China)
Publisher:   Elsevier Science Publishing Co Inc
Edition:   2nd edition
ISBN:  

9780128203538


Pages:   608
Publication Date:   09 April 2021
Format:   Paperback
Availability:   In Print   Availability explained
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Intelligent Image and Video Compression: Communicating Pictures


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Author:   David Bull (University of Bristol, UK) ,  Fan Zhang (School of Astronautics, Northwestern Polytechnical University, China)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Edition:   2nd edition
Weight:   1.000kg
ISBN:  

9780128203538


ISBN 10:   0128203536
Pages:   608
Publication Date:   09 April 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Introduction 2. The human visual system 3. Signal processing and information theory fundamentals 4. Digital picture formats and representations 5. Transforms for image and video coding 6. Filter banks and wavelet compression 7. Lossless compression methods 8. Coding moving pictures: Motion prediction 9. The block-based hybrid video codec 10. Measuring and managing picture quality 11. Communicating pictures: Delivery across networks 12. Video coding standards and formats 13. Communicating pictures - the future

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Author Information

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. 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.

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