Digital Signal Processing Reference
In-Depth Information
Lossy
Lossy image compression is used in digital cameras, to increase storage capacities with
minimal degradation of picture quality. Similarly, DVDs use the lossy MPEG-2 Video
codec for video compression.
In lossy audio compression, methods of psychoacoustics are used to remove non-audible
(or less audible) components of the signal. Compression of human speech is often
performed with even more specialized techniques, so that "speech compression" or "voice
coding" is sometimes distinguished as a separate discipline from "audio compression".
Different audio and speech compression standards are listed under audio codecs. Voice
compression is used in Internet telephony for example, while audio compression is used
for CD ripping and is decoded by audio players.
Lossless
The Lempel-Ziv (LZ) compression methods are among the most popular algorithms for
lossless storage. DEFLATE is a variation on LZ which is optimized for decompression
speed and compression ratio, therefore compression can be slow. DEFLATE is used in
PKZIP, gzip and PNG. LZW (Lempel-Ziv-Welch) is used in GIF images. Also
noteworthy are the LZR (LZ-Renau) methods, which serve as the basis of the Zip
method. LZ methods utilize a table-based compression model where table entries are
substituted for repeated strings of data. For most LZ methods, this table is generated
dynamically from earlier data in the input. The table itself is often Huffman encoded (e.g.
SHRI, LZX). A current LZ-based coding scheme that performs well is LZX, used in
Microsoft's CAB format.
The very best modern losless compressors use probabilistic models, such as prediction by
partial matching. The Burrows-Wheeler transform can also be viewed as an indirect form
of statistical modelling.
In a further refinement of these techniques, statistical predictions can be coupled to an
algorithm called arithmetic coding. Arithmetic coding, invented by Jorma Rissanen, and
turned into a practical method by Witten, Neal, and Cleary, achieves superior
compression to the better-known Huffman algorithm, and lends itself especially well to
adaptive data compression tasks where the predictions are strongly context-dependent.
Arithmetic coding is used in the bilevel image-compression standard JBIG, and the
document-compression standard DjVu. The text
entry
system, Dasher, is an inverse-
arithmetic-coder.
Theory
The theoretical background of compression is provided by information theory (which is
closely related to algorithmic information theory) for lossless compression, and by rate-
distortion theory for lossy compression. These fields of study were essentially created by
Claude Shannon, who published fundamental papers on the topic in the late 1940s and
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