A major difference between multimedia data and most other data is its size. Images and audio files take much more space than text, for example. Video data is currently the single largest network bandwidth and hard disk space consumer. Compression was, therefore, among the first issues researchers in the emerging multimedia field sought to address. In fact, multimedia’s history is closely connected to different compression algorithms because they served as enabling technologies for many applications. Even today, multimedia signal processing would not be possible without compression methods. A Blu-ray disc can currently store 50 Gbytes, but a ninety-minute movie in 1,080p HDTV format takes about 800 Gbytes (without audio). So how does it fit on the disc? The answer to many such problems is compression.
This chapter discusses the underlying mathematical principles of compression algorithms, from the basics to advanced techniques. However, all the techniques outlined in this chapter belong to the family of lossless compression techniques; that is, the original data can be reconstructed bit by bit. Lossless compression techniques are applicable to all kinds of data, including non-multimedia data. However, these techniques are not always effective with all types of data. Therefore, subsequent chapters will introduce lossy compression techniques that are usually tailored to a specific type of data, for example, image or sound files.
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