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In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".
Group 4 compression is based on the Group 3 two-dimensional compression scheme (G3-2D), also known as Modified READ, which is in turn based on the Group 3 one-dimensional compression scheme (G3), also known as Modified Huffman coding. Group 4 compression is available in many proprietary image file formats as well as standardized formats such as ...
Canonical Huffman codes address these two issues by generating the codes in a clear standardized format; all the codes for a given length are assigned their values sequentially. This means that instead of storing the structure of the code tree for decompression only the lengths of the codes are required, reducing the size of the encoded data.
In computing, Deflate (stylized as DEFLATE, and also called Flate [1] [2]) is a lossless data compression file format that uses a combination of LZ77 and Huffman coding.It was designed by Phil Katz, for version 2 of his PKZIP archiving tool.
The package-merge algorithm is an O(nL)-time algorithm for finding an optimal length-limited Huffman code for a given distribution on a given alphabet of size n, where no code word is longer than L. It is a greedy algorithm, and a generalization of Huffman's original algorithm.
A compression format using LZMA2 to yield high compression ratios. The LZMA algorithm is an LZ77 derivative, with entropy encoding in the form of range encoding. .z application/ x-compress: pack: Unix-like The traditional Huffman coding compression format. .Z application/ x-compress: compress: Unix-like The traditional LZW compression format ...
ANS combines the compression ratio of arithmetic coding (which uses a nearly accurate probability distribution), with a processing cost similar to that of Huffman coding. In the tabled ANS (tANS) variant, this is achieved by constructing a finite-state machine to operate on a large alphabet without using multiplication.
Lempel–Ziv–Storer–Szymanski (LZSS) is a lossless data compression algorithm, a derivative of LZ77, that was created in 1982 by James A. Storer and Thomas Szymanski. LZSS was described in article "Data compression via textual substitution" published in Journal of the ACM (1982, pp. 928–951). [1] LZSS is a dictionary coding technique. It ...