{"product_id":"9783032352651","title":"Video Compression Theory and Practice Neural and AI-Native Video Compression","description":"\u003ch1\u003eVideo Compression Theory and Practice\u003c\/h1\u003e\u003ch2\u003eNeural and AI-Native Video Compression\u003c\/h2\u003e\u003ch3\u003eReka Sandaruwan Gallena Watthage | Anil Fernando\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Interactive \u0026amp; Multimedia\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003eThis book aims to bridge the increasing gap that has emerged between the classical principles of compression and the rapidly growing world of AI-driven and neural video coding. The acceleration ongoing in the area urgently requires an integrated reference that links theoretical underpinning with practical realities of modern media systems. This book intends to bring the different threads of royalty-bearing and royalty-free codec ecosystems together, set the compression research in perspective against real-life applications that span from large-scale streaming services to immersive VR\/AR environments.\u003c\/p\u003e\n\u003cp\u003eThe need for such a book has never been greater. Video now constitutes more than 80% of global internet traffic, fuelled by an explosion of 4K\/8K, HDR, VR, and AR content. Streaming platforms deliver billions of viewing hours each day, placing unprecedented pressure on network infrastructure. Without continual advances in compression, the global internet would struggle to sustain the accelerating demand. At the same time, the technology landscape has become fragmented and fast-moving: H.264 evolved into H.265, H.266\/VVC, and onward to AV1, AV2, and emerging neural codecs, while industry continues to navigate conflicting ecosystems of patent-encumbered standards and royalty-free alternatives. These codecs also serve increasingly diverse use cases-streaming, broadcasting, video conferencing, immersive media, autonomous systems-yet no single resource explains how these technologies relate, compare, and complement one another.\u003c\/p\u003e\n\u003cp\u003eThe main challenges that come with this are: engineering teams struggle to pick codecs that are suitable, developers employ implementations without necessarily understanding the underlying theory behind it, and decision-makers make infrastructure decisions at scale without a comprehensive technical framework. Researchers often work in silos: traditional compression communities and AI-based communities rarely interact with each other, despite clear opportunities for synergy. These educational gaps are accentuated further: university curricula often stop at H.264 or introductory concepts, existing textbooks are either outdated or narrow, and professional training resources are often proprietary, expensive, or incomplete. In turn, this means that graduates and new engineers enter the field unprepared for the modern video technology stack.\u003c\/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003eThis book addresses critical needs on both the technical and broader landscape. Standards professionals must have a coherent historical and technical context; open-source developers seek to understand codec internals in depth; the task of streaming engineers is to optimize end-to-end systems. Beyond the technical community, efficient compression has direct societal impact, including providing access to video in bandwidth-constrained regions, supporting sustainability through reducing energy consumption in data centers preserving digital heritage, and driving innovation across sectors. Existing literature suffers from several shortcomings: highly theoretical, too narrow, outdated, siloed by application, or entirely separate between traditional and AI-based approaches. Video Compression Theory and Practices cover everything from foundational theory to modern AI models, practical insights into implementation, and comparative analysis of recent standards introduced between 2020 and 2025. The book combines academic rigor with industrial pragmatism and shows how fifty years of compression research have informed today's hybrid and neural codecs.\u003c\/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cp\u003eReka is a member of the Department of Computer and Information Sciences at the University of Strathclyde, where he conducts research under the supervision of Professor Anil Fernando. He is committed to advancing AI-native video coding while making complex video compression concepts accessible to researchers and practitioners.\u003cbr\u003eBeyond academia, he has more than twelve years of experience in the IT and software industry with expertise in C\/C++, cloud engineering, cloud architecture, distributed systems, and Service-Oriented Architecture. He has contributed to major open-source initiatives including the Apache HTTP Server and the FOSS Sahana Disaster Management System developed by the Lanka Software. His industrial background strongly influences his research on scalable cloud-native video streaming and adaptive bitrate delivery systems.\u003cbr\u003eHe has extensive teaching experience at the University of Strathclyde as a Teaching Assistant and Lab Demonstrator across more than fifteen undergraduate and postgraduate modules, including Topics in Computing, Computer Systems and Architecture, Building Software Systems, Information Access and Mining, Big Data Fundamentals, Large Language Models, Image Processing, Computer Vision, Foundations of Artificial Intelligence, Logic and Algorithms, Health and Care Data Analytics, and Mobile App Development. Previously, he served as a Visiting Lecturer at the University of Moratuwa and the Sri Lankan branch of Massey University, where he taught C Programming, Fundamentals of Computing, Digital Image Processing, Computer Vision, and Artificial Neural Networks.\u003cbr\u003eProfessor Anil Fernando is Professor of Video Coding and Communications in the Department of Computer and Information Sciences at the University of Strathclyde, Glasgow, where he leads the Video Coding and Communication Research Team. He received his B.Sc. (First Class) from the University of Moratuwa, M.Sc. (Distinction) from the Asian Institute of Technology, and Ph.D. from the University of Bristol. His research spans video coding, machine learning, semantic communications, signal processing, networking, interactive systems, 5G\/6G resource optimization, distributed technologies, media broadcasting, and Quality of Experience (QoE). He has supervised over 120 Ph.D. graduates and more than 32 research fellows, published over 450 papers and a book on 3D video broadcasting, and received the IEEE International Shall Award and the NAB 2020 Award. His research collaborations include the BBC, European broadcasters, media companies, and international multidisciplinary projects covering AI-driven media, immersive communications, automated driving, virtual and augmented reality, video coding for machines, and next-generation intelligent media systems.\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e11 January 2027\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Switzerland\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032352651\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e517\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":51324790341772,"sku":"9783032352651","price":80.99,"currency_code":"USD","in_stock":true}],"url":"https:\/\/lateknightbooks.com\/products\/9783032352651","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}