Methods of Signal Compression

Abstract

This chapter introduces fundamental concepts of signal coding, as they are commonly applied for various types of multimedia signals (image, video, graphics, audio, speech) and associated components (e.g. depth maps of images/video). A common property is correlation between samples, which can be removed by signal processing, performing a mapping into an equivalent representation which exposes less statistical dependencies between samples and is sparse, i.e. concentrating information in few relevant samples. The main approaches for this are predictive coding, where the original signal is mapped to a prediction error signal, and transform coding, where a mapping into transform coefficients is made. Sparseness is important, as it allows representing many values by zero, which can be encoded quite efficiently. On the other hand, multimedia signals can hardly be classified as stationary random processes, they typically change local statistical properties. Therefore, adaptation of the compression methods is important, both in predictive and in transform coding. Though the methods of adaptation are often specific for a certain type of multimedia signals and are with more detail discussed in upcoming chapters, common principles are introduced here.