Motion Estimation Algorithms for Video Compression - Borko Furht

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Résumé :
1. The Problem of Video Compression.- 1.1 Storage and Bandwidth Requirements for Multimedia.- 1.2 Multimedia and Compression.- 1.3 Image and Video Formats.- 1.4 Overview of the Book.- 2. Video Compression Techniques.- 2.1 JPEG Image Compression and Motion JPEG.- 2.2 Fractal Image Compression.- 2.3 Wavelet-Based Compression.- 2.4 The H.261/H.263 Compression Standard.- 2.5 MPEG Video Compression Standard.- 2.6 Applications of Compressed Video.- 3. Motion Compensation and Estimation.- 3.1 Motion Compensation in MPEG.- 3.2 Principles of Block-Matching Motion Estimation.- 3.3 Cost Functions.- 3.4 Motion Vector Search Algorithms.- 3.5 Complexity of Motion Estimation Algorithms.- 4. Experiments on Current Motion Estimation Techniques.- 4.1 Analysis of Pattern of Motion.- 4.2 Comparison of Current Search Algorithms and Cost Functions.- 4.3 Impact of the Search Parameter.- 4.4 Visual Output Data.- 4.5 Summary of Results.- 5. The Motion Compensation Hypothesis.- 5.1 The Motion Compensation Assumptions.- 5.2 Testing the Motion Hypothesis.- 6. Fast Search Algorithms: New Results.- 6.1 The Need for Fast Search Algorithms.- 6.2 The Fast Search Hypothesis.- 6.3 The One-Pixel Greedy Search Algorithm.- 6.4 The Densely-Centered Uniform P-Search Algorithm.- 6.5 Comparison of Fast Search Algorithms.- 7. Conclusions and Research Directions....

Biographie:
Nataliia Neshenko, Ph.D., FCCA, PMP, PMI-ACP is Visiting Instructor at the Department of Information Technology and Operations Management (ITOM) at the College of Business, Florida Atlantic University. Her research focus is operational cybersecurity, including attack detection and characterization, risk management methodologies, the Internet of Things, and visual data mining and analysis. Her research findings are published in leading refereed security and data science journals and conferences. Dr. Neshenko is a recipient of the Best Paper Award at the 2017 IEEE International Symposium on Personal Indoor and Mobile Radio Communications. She also has over 16 years of project management experience in the field of business optimization in finance and IT. Bou-Harb, Ph.D., CISSP received a Ph.D. degree in computer science from Concordia University, Montreal, Canada. He was a visiting research scientist at Carnegie Mellon University (CMU), Pittsburgh, PA, USA, in 2015-2016. He is currently the Director of The Cyber Center For Security and Analytics at the University of Texas at San Antonio (UTSA) and an Associate Professor at the Department of Information Systems and Cyber Security. Dr. Bou-Harb specializes in operational cyber security and data science as applicable to the national security challenge. He is also a research scientist at the National Cyber Forensic and Training Alliance (NCFTA) of Canada. His current research interests are operational cyber security, attack detection and characterization, Internet measurements, and cyber security for critical infrastructure. Dr. Bou-Harb has authored more than 120 refereed publications in leading security and data science venues...

Sommaire:
Video technology promises to be the key for the transmission of motion video. A number of video compression techniques and standards have been introduced in the past few years, particularly the MPEG-1 and MPEG-2 for interactive multimedia and for digital NTSC and HDTV applications, and H.2611H.263 for video telecommunications. These techniques use motion estimation techniques to reduce the amount of data that is stored and transmitted for each frame. This book is about these motion estimation algorithms, their complexity, implementations, advantages, and drawbacks. First, we present an overview of video compression techniques with an emphasis to techniques that use motion estimation, such as MPEG and H.2611H.263. Then, we give a survey of current motion estimation search algorithms, including the exhaustive search and a number of fast search algorithms. An evaluation of current search algorithms, based on a number of experiments on several test video sequences, is presented as well. The theoretical framework for a new fast search algorithm, Densely-Centered Uniform-P Search (DCUPS), is developed and presented in the book. The complexity of the DCUPS algorithm is comparable to other popular motion estimation techniques, however the algorithm shows superior results in terms of compression ratios and video qUality. We should stress out that these new results, presented in Chapters 4 and 5, have been developed by Joshua Greenberg, as part of his M.Sc. thesis entitled Densely-Centered Uniform P-Search: A Fast Motion Estimation Algorithm (FAU, 1996)....