Motion Estimation For Video Coding

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.

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.

What is Motion Estimation In computer vision and image processing, motion estimation is the process of determining motion vectors that describe the transformation from one 2D image to another; usually from adjacent frames in a video sequence. It is an ill-posed problem as the motion happens in three dimensions (3D) but the images are a projection of the 3D scene onto a 2D plane. The motion vectors may relate to the whole image or specific parts, such as rectangular blocks, arbitrary shaped patches or even per pixel. The motion vectors may be represented by a translational model or many other models that can approximate the motion of a real video camera, such as rotation and translation in all three dimensions and zoom. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Motion_estimation Chapter 2: Motion_compensation Chapter 3: Block-matching_algorithm Chapter 4: H.261 Chapter 5: H.262/MPEG-2_Part_2 Chapter 6: Advanced_Video_Coding Chapter 7: Global_motion_compensation Chapter 8: Block-matching_and_3D_filtering Chapter 9: Video_compression_picture_types Chapter 10: Video_super-resolution (II) Answering the public top questions about motion estimation. (III) Real world examples for the usage of motion estimation in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Motion Estimation.

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).

MPEG-4 is the multimedia standard for combining interactivity, natural and synthetic digital video, audio and computer-graphics. Typical applications are: internet, video conferencing, mobile videophones, multimedia cooperative work, teleteaching and games. With MPEG-4 the next step from block-based video (ISO/IEC MPEG-1, MPEG-2, CCITT H.261, ITU-T H.263) to arbitrarily-shaped visual objects is taken. This significant step demands a new methodology for system analysis and design to meet the considerably higher flexibility of MPEG-4. Motion estimation is a central part of MPEG-1/2/4 and H.261/H.263 video compression standards and has attracted much attention in research and industry, for the following reasons: it is computationally the most demanding algorithm of a video encoder (about 60-80% of the total computation time), it has a high impact on the visual quality of a video encoder, and it is not standardized, thus being open to competition. Algorithms, Complexity Analysis, and VLSI Architectures for MPEG-4 Motion Estimation covers in detail every single step in the design of a MPEG-1/2/4 or H.261/H.263 compliant video encoder: Fast motion estimation algorithms Complexity analysis tools Detailed complexity analysis of a software implementation of MPEG-4 video Complexity and visual quality analysis of fast motion estimation algorithms within MPEG-4 Design space on motion estimation VLSI architectures Detailed VLSI design examples of (1) a high throughput and (2) a low-power MPEG-4 motion estimator. Algorithms, Complexity Analysis and VLSI Architectures for MPEG-4 Motion Estimation is an important introduction to numerous algorithmic, architectural and system design aspects of the multimedia standard MPEG-4. As such, all researchers, students and practitioners working in image processing, video coding or system and VLSI design will find this book of interest.

Motion estimation is a key issue in the field of moving images analysis. In the framework of video coding, it is combined with motion compensation in order to exploit the spatio temporal correlation of image sequences along the motion trajectory. It then achieves one of the most important compression factors of a video coder. By dividing each frame into rectangular blocks, motion vectors are obtained via the block matching algorithms (BMA). The full search algorithm (FS) is a brute force BMA. It searches all possible locations inside the search window in the reference frame to provide an optimal solution. However, its high computational complexity makes it often not suitable for real-time implementation. Many fast but sub-optimal algorithms are introduced to improve the performance of video coders. The present book analyses three prospects of improving the quality of existing video coding schemes. Namely, one at a time optimization, adaptive search stagey and feature domain based criteria.

Multi-Frame Motion-Compensated Prediction for Video Transmission presents a comprehensive description of a new technique in video coding and transmission. The work presented in the book has had a very strong impact on video coding standards and will be of interest to practicing engineers and researchers as well as academics. The multi-frame technique and the Lagrangian coder control have been adopted by the ITU-T as an integral part of the well known H.263 standard and are were adopted in the ongoing H.26L project of the ITU-T Video Coding Experts Group. This work will interest researchers and students in the field of video coding and transmission. Moreover, engineers in the field will also be interested since an integral part of the well known H.263 standard is based on the presented material.

Appendices 133 A Mathematical Results 133 A.1 Singularities of the Displacement Error Covariance Matrix 133 A.2 A Class of Matrices and their Eigenvalues 134 A.3 Inverse of the Power Spectral Density Matrix 134 A.4 Power Spectral Density of a Frame 136 Glossary 137 References 141 Index 159 Preface This book aims to capture recent advances in motion compensation for - ficient video compression. It investigates linearly combined motion comp- sated signals and generalizes the well known superposition for bidirectional prediction in B-pictures. The number of superimposed signals and the sel- tion of reference pictures will be important aspects of the discussion. The application oriented part of the book employs this concept to the well known ITU-T Recommendation H.263 and continues with the improvements by superimposed motion-compensated signals for the emerging ITU-T R- ommendation H.264 and ISO/IEC MPEG-4 (Part 10). In addition, it discusses a new approach for wavelet-based video coding. This technology is currently investigated by MPEG to develop a new video compression standard for the mid-term future.