Name
Abstract | ||
|---|---|---|
Arithmetic coding is a data compression technique that encodes data (the data string) by creating a code string which represents a fractional value on the number line between 0 and 1. The coding algorithm is symbolwise recursive; i.e., it operates upon and encodes (decodes) one data symbol per iteration or recursion. On each recursion, the algorithm successively partitions an interval of the number line between 0 and 1, and retains one of the partitions as the new interval. Thus, the algorithm successively deals with smaller intervals, and the code string, viewed as a magnitude, lies in each of the nested intervals. The data string is recovered by using magnitude comparisons on the code string to recreate how the encoder must have successively partitioned and retained each nested subinterval. Arithmetic coding differs considerably from the more familiar compression coding techniques, such as prefix (Huffman) codes. Also, it should not be confused with error control coding, whose object is to detect and correct errors in computer operations. This paper presents the key notions of arithmetic compression coding by means of simple examples. |
Year | DOI | Venue |
|---|---|---|
1984 | 10.1147/rd.282.0135 | IBM Journal of Research and Development |
Keywords | Field | DocType |
data compression technique,error control coding,code string,data symbol,data string,number line,arithmetic compression,encodes data,arithmetic coding,coding algorithm | Tunstall coding,Entropy encoding,Context-adaptive variable-length coding,Computer science,Algorithm,Huffman coding,Shannon–Fano coding,Arithmetic coding,Context-adaptive binary arithmetic coding,Variable-length code | Journal |
Volume | Issue | ISSN |
28 | 2 | 0018-8646 |
Citations | PageRank | References |
174 | 58.54 | 14 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Glen G. Langdon | 1 | 209 | 82.77 |