The book deals with the development of a methodology to estimate the motion field between two frames for video coding applications. This book proposes an exhaustive study of the motion estimation process in the framework of a general video coder. The conceptual explanations are discussed in a simple language and with the use of suitable figures. The book will serve as a guide for new researchers working in the field of motion estimation techniques.
Real-Time Video Compression: Techniques and Algorithms introduces the XYZ video compression technique, which operates in three dimensions, eliminating the overhead of motion estimation. First, video compression standards, MPEG and H.261/H.263, are described. They both use asymmetric compression algorithms, based on motion estimation. Their encoders are much more complex than decoders. The XYZ technique uses a symmetric algorithm, based on the Three-Dimensional Discrete Cosine Transform (3D-DCT). 3D-DCT was originally suggested for compression about twenty years ago; however, at that time the computational complexity of the algorithm was too high, it required large buffer memory, and was not as effective as motion estimation. We have resurrected the 3D-DCT-based video compression algorithm by developing several enhancements to the original algorithm. These enhancements make the algorithm feasible for real-time video compression in applications such as video-on-demand, interactive multimedia, and videoconferencing. The demonstrated results, presented in this book, suggest that the XYZ video compression technique is not only a fast algorithm, but also provides superior compression ratios and high quality of the video compared to existing standard techniques, such as MPEG and H.261/H.263. The elegance of the XYZ technique is in its simplicity, which leads to inexpensive VLSI implementation of any XYZ codec. Real-Time Video Compression: Techniques and Algorithms can be used as a text for graduate students and researchers working in the area of real-time video compression. In addition, the book serves as an essential reference for professionals in the field.
In recent years there has been an increasing interest in Second Generation Image and Video Coding Techniques. These techniques introduce new concepts from image analysis that greatly improve the performance of the coding schemes for very high compression. This interest has been further emphasized by the future MPEG 4 standard. Second generation image and video coding techniques are the ensemble of approaches proposing new and more efficient image representations than the conventional canonical form. As a consequence, the human visual system becomes a fundamental part of the encoding/decoding chain. More insight to distinguish between first and second generation can be gained if it is noticed that image and video coding is basically carried out in two steps. First, image data are converted into a sequence of messages and, second, code words are assigned to the messages. Methods of the first generation put the emphasis on the second step, whereas methods of the second generation put it on the first step and use available results for the second step. As a result of including the human visual system, second generation can be also seen as an approach of seeing the image composed by different entities called objects. This implies that the image or sequence of images have first to be analyzed and/or segmented in order to find the entities. It is in this context that we have selected in this book three main approaches as second generation video coding techniques: Segmentation-based schemes Model Based Schemes Fractal Based Schemes £/LIST£ Video Coding: The Second Generation Approach is an important introduction to the new coding techniques for video. As such, all researchers, students and practitioners working in image processing will find this book of interest.
Over the years, thousands of engineering students and professionals relied on Digital Video Processing as the definitive, in-depth guide to digital image and video processing technology. Now, Dr. A. Murat Tekalp has completely revamped the first edition to reflect today’s technologies, techniques, algorithms, and trends. Digital Video Processing, Second Edition, reflects important advances in image processing, computer vision, and video compression, including new applications such as digital cinema, ultra-high-resolution video, and 3D video. This edition offers rigorous, comprehensive, balanced, and quantitative coverage of image filtering, motion estimation, tracking, segmentation, video filtering, and compression. Now organized and presented as a true tutorial, it contains updated problem sets and new MATLAB projects in every chapter. Coverage includes Multi-dimensional signals/systems: transforms, sampling, and lattice conversion Digital images and video: human vision, analog/digital video, and video quality Image filtering: gradient estimation, edge detection, scaling, multi-resolution representations, enhancement, de-noising, and restoration Motion estimation: image formation; motion models; differential, matching, optimization, and transform-domain methods; and 3D motion and shape estimation Video segmentation: color and motion segmentation, change detection, shot boundary detection, video matting, video tracking, and performance evaluation Multi-frame filtering: motion-compensated filtering, multi-frame standards conversion, multi-frame noise filtering, restoration, and super-resolution Image compression: lossless compression, JPEG, wavelets, and JPEG2000 Video compression: early standards, ITU-T H.264/MPEG-4 AVC, HEVC, Scalable Video Compression, and stereo/multi-view approaches
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).
A discussion of a compressed-domain approach for designing and implementing digital video coding systems, which is drastically different from the traditional hybrid approach. It demonstrates how the combination of discrete cosine transform (DCT) coders and motion compensated (MC) units reduces power consumption and hardware complexity.
Multidimensional Signal, Image, and Video Processing and Coding gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. Multidimensional Signal, Image, and Video Processing and Coding also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: - New appendices on random processes, information theory - New coverage of image analysis – edge detection, linking, clustering, and segmentation - Expanded coverage on image sensing and perception, including color spaces - Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC - Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding - More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming - New coverage of super-resolution methods for image and video - Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected - New chapters on introductory random processes, information theory, and image enhancement and analysis - Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC)
This book provides developers, engineers, researchers and students with detailed knowledge about the High Efficiency Video Coding (HEVC) standard. HEVC is the successor to the widely successful H.264/AVC video compression standard, and it provides around twice as much compression as H.264/AVC for the same level of quality. The applications for HEVC will not only cover the space of the well-known current uses and capabilities of digital video – they will also include the deployment of new services and the delivery of enhanced video quality, such as ultra-high-definition television (UHDTV) and video with higher dynamic range, wider range of representable color, and greater representation precision than what is typically found today. HEVC is the next major generation of video coding design – a flexible, reliable and robust solution that will support the next decade of video applications and ease the burden of video on world-wide network traffic. This book provides a detailed explanation of the various parts of the standard, insight into how it was developed, and in-depth discussion of algorithms and architectures for its implementation.
In order for wireless devices to function, the signals must be coded in standard ways so that the sender and the receiver can communicate. This area of video source coding is one of the key challenges in the worldwide push to deliver full video communications over wireless devices. Video Coding for Mobile Communications reviews current progress in this field and looks at how to solve some of the most important technology issues in the months and years ahead. The vision of being able to communicate from anywhere, at any time, and with any type of information is on its way to becoming reality. This natural convergence of mobile communications and multimedia is a field that is expected to achieve unprecedented growth and commercial success. Current wireless communication devices support a number of basic multimedia services (voice, messages, basic internet access), but have coding problems that need to be solved before "real-time" mobile video communication can be achieved. - Addresses the emerging field of mobile multimedia communications
The need of video compression in the modern age of visual communication cannot be over-emphasized. This monograph will provide useful information to the postgraduate students and researchers who wish to work in the domain of VLSI design for video processing applications. In this book, one can find an in-depth discussion of several motion estimation algorithms and their VLSI implementation as conceived and developed by the authors. It records an account of research done involving fast three step search, successive elimination, one-bit transformation and its effective combination with diamond search and dynamic pixel truncation techniques. Two appendices provide a number of instances of proof of concept through Matlab and Verilog program segments. In this aspect, the book can be considered as first of its kind. The architectures have been developed with an eye to their applicability in everyday low-power handheld appliances including video camcorders and smartphones.
