Compression of Digital Data Explained in an Understandable Way (essentials)
With today's flood of data circulating on storage media and the Internet, compression of digital data remains an immensely important aspect of data transmission and storage. This essential explains, without theoretical superstructure and with elementary mathematical methods, the most important compression methods, such as the entropy encodings of Shannon-Fano and of Huffman, as well as the dictionary encodings of the Lempel-Ziv family. Irrelevance reduction and quantization for optical and acoustic signals, which exploit the inadequacies of the human eye and ear for data compression, are also discussed in detail. The whole is illustrated by means of common practical applications from the everyday environment. The presentation allows the use, for example, in working groups at schools, in introductory courses at universities and is also suitable for interested laypersons.