Abstract Most data that is inherently discrete needs to be compressed in such a way that it can be recovered exactly, without any loss. Examples include text of all kinds, experimental results, and statistical databases. Other forms of data may need to be stored exactly, such as images---particularly bilevel ones, or ones arising in medical and remotesensing applications, or ones that may be required to be certified true for legal reasons. Moreover, during the process of lossy compression, many occasions for lossless compression of coefficients or other information arise. This paper surveys techniques for lossless compression. The process of compression can be broken down into modeling and coding. We provide an extensive discussion of coding techniques, and then introduce methods of modeling that are appropriate for text and images. Standard methods used in popular utilities (in the case of text) and international standards (in the case of images) are described.
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2739
|
A mathematical theory of communication
– Shannon
- 1948
|
|
760
|
A universal algorithm for sequential data compression
– Lempel, Ziv
- 1977
|
|
578
|
A method for the construction of minimum redundancy codes
– Huffman
- 1952
|
|
564
|
Managing Gigabytes: Compressing and Indexing Documents and Images
– Witten, Bell, et al.
- 1994
|
|
523
|
Arithmetic coding for data compression
– Witten, Neal, et al.
- 1987
|
|
481
|
Compression of individual sequences via variable-rate coding
– Ziv, Lempel
- 1978
|
|
325
|
A Technique for High-Performance Data Compression
– Welch
- 1984
|
|
293
|
A block-sorting lossless data compression algorithm
– Burrows, Wheeler
- 1994
|
|
251
|
Data Compression Using Adaptive Coding and Partial String Matching
– Cleary, Witten
- 1984
|
|
223
|
Universal codeword sets and representations of the integers
– Elias
- 1975
|
|
207
|
Prediction and entropy of printed English
– Shannon
- 1951
|
|
161
|
Run-length encodings
– Golomb
- 1966
|
|
148
|
Arithmetic coding
– Langdon
- 1979
|
|
108
|
Arithmetic Coding Revisited
– Moffat, Neal, et al.
- 1998
|
|
100
|
Implementing the ppm data compression scheme,” in
– Moffat
- 1990
|
|
96
|
Universal modeling and coding
– Rissanen, Langdon
- 1981
|
|
87
|
on a theme by Huffman
– “Variations
- 1978
|
|
85
|
Unbounded length contexts for PPM
– Cleary, Teahan, et al.
- 1995
|
|
82
|
Dynamic Huffman coding
– Knuth
- 1985
|
|
80
|
Data compression via textual substitution
– Storer, Szymanski
- 1982
|
|
78
|
An overview of the basic principles of the q-coder adaptative binary arithmetic coder
– Pennebaker, Mitchell, et al.
- 1988
|
|
70
|
Data compression in full-text retrieval systems
– Bell, Moffat, et al.
- 1993
|
|
68
|
Data Compression using Dynamic Markov Modelling
– Cormack, Horspool
- 1987
|
|
68
|
Optimal source codes for geometrically distributed integer alphabets
– Gallager, Voorhis
- 1975
|
|
68
|
Generalized Kraft Inequality and Arithmetic Coding
– Rissanen
- 1976
|
|
58
|
Data compression with finite windows
– Fiala, Greene
- 1989
|
|
48
|
Some practical universal noiseless coding techniques
– Rice, Lee
- 1983
|
|
44
|
The Design and Analysis of Efficient Lossless Data Compression Systems
– Howard
- 1993
|
|
37
|
A convergent gambling estimate of the entropy of English
– Cover, King
- 1978
|
|
34
|
Fast and efficient lossless image compression
– Vitter, Howard
- 1993
|
|
31
|
A fast algorithm for optimal length-limited Huffman codes
– Larmore, Hirschberg
- 1990
|
|
29
|
On the construction of Huffman trees
– Leeuwen
- 1976
|
|
29
|
An Extremely Fast Ziv-Lempel Data Compression Algorithm Data Compression Conference
– Williams
- 1991
|
|
28
|
Efficient decoding of prefix codes
– Hirschberg, Lelewer
- 1990
|
|
28
|
On the Implementation of Minimum Redundancy Prefix Codes
– Moffat, Turpin
- 1997
|
|
28
|
Generating a canonical prefix encoding
– Schwartz, Kallick
- 1964
|
|
27
|
A note on Ziv–Lempel model for compressing individual sequences
– Langdon
- 1983
|
|
27
|
Probability estimation for the Q-coder
– Pennebaker, Mitchell
- 1988
|
|
24
|
Bounds on the redundancy of Huffman codes
– Capocelli, Giancarlo, et al.
- 1986
|
|
24
|
Optimal computer search trees and variable length alphabetic codes
– Hu, Tucker
- 1971
|
|
24
|
International Digital Facsimile Coding Standards
– Hunter, Robinson
- 1980
|
|
24
|
Application of Splay Trees to Data Compression
– Jones
- 1988
|
|
23
|
In-place calculation of minimum-redundancy codes
– Moffat, Katajainen
- 1995
|
|
22
|
Practical implementations of arithmetic coding
– Howard, Vitter
- 1992
|
|
22
|
Parameterised compression for sparse bitmaps
– Moffat, Zobel
- 1992
|
|
21
|
The zero frequency problem: Estimating the probabilities of novel events in adaptive text compression
– Witten, Bell
- 1991
|
|
20
|
A Multiplication-Free Multialphabet Arithmetic Code
– Rissanen, Mohiuddin
- 1989
|
|
20
|
Computing a minimum-weight k-link path in graphswith the concave monge property
– Schieber
- 1995
|
|
18
|
The effect of non-greedy parsing in Ziv-Lempel compression methods
– Horspool
- 1995
|
|
18
|
A context-based, adaptive, lossless/nearly-lossless coding scheme for continuous-tone images
– Wu, Memon, et al.
- 1995
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