Source Coding: Part I of Fundamentals of Source and Video Coding

Thomas Wiegand
2010 Foundations and Trends® in Signal Processing  
Digital media technologies have become an integral part of the way we create, communicate, and consume information. At the core of these technologies are source coding methods that are described in this monograph. Based on the fundamentals of information and rate distortion theory, the most relevant techniques used in source coding algorithms are described: entropy coding, quantization as well as predictive and transform coding. The emphasis is put onto algorithms that are also used in video
more » ... ing, which will be explained in the other part of this two-part monograph. • throughput of the channel: a characteristic influenced by the transmission channel bit rate and the amount of protocol 1.2 Scope and Overview of the Text 5 coding. This means that we will leave out a number of areas including implementation aspects of video coding and the whole subject of video transmission and error-robust coding. The monograph is divided into two parts. In the first part, the fundamentals of source coding are introduced, while the second part explains their application to modern video coding. Source Coding Fundamentals. In the present first part, we describe basic source coding techniques that are also found in video codecs. In order to keep the presentation simple, we focus on the description for one-dimensional discrete-time signals. The extension of source coding techniques to two-dimensional signals, such as video pictures, will be highlighted in the second part of the text in the context of video coding. Section 2 gives a brief overview of the concepts of probability, random variables, and random processes, which build the basis for the descriptions in the following sections. In Section 3, we explain the fundamentals of lossless source coding and present lossless techniques that are found in the video coding area in some detail. The following sections deal with the topic of lossy compression. Section 4 summarizes important results of rate distortion theory, which builds the mathematical basis for analyzing the performance of lossy coding techniques. Section 5 treats the important subject of quantization, which can be considered as the basic tool for choosing a trade-off between transmission bit rate and signal fidelity. Due to its importance in video coding, we will mainly concentrate on the description of scalar quantization. But we also briefly introduce vector quantization in order to show the structural limitations of scalar quantization and motivate the later discussed techniques of predictive coding and transform coding. Section 6 covers the subject of prediction and predictive coding. These concepts are found in several components of video codecs. Wellknown examples are the motion-compensated prediction using previously coded pictures, the intra prediction using already coded samples inside a picture, and the prediction of motion parameters. In Section 7, we explain the technique of transform coding, which is used in most video codecs for efficiently representing prediction error signals.
doi:10.1561/2000000010 fatcat:tm2z3ytnmrajnpbgoakqka6wj4