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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".
Instructions to generate the necessary Huffman tree immediately follow the block header. The static Huffman option is used for short messages, where the fixed saving gained by omitting the tree outweighs the percentage compression loss due to using a non-optimal (thus, not technically Huffman) code. Compression is achieved through two steps:
When naively Huffman coding binary strings, no compression is possible, even if entropy is low (e.g. ({0, 1}) has probabilities {0.95, 0.05}). Huffman encoding assigns 1 bit to each value, resulting in a code of the same length as the input. By contrast, arithmetic coding compresses bits well, approaching the optimal compression ratio of
It is tunable with compression levels ranging from negative 7 (fastest) [6] to 22 (slowest in compression speed, but best compression ratio). Starting from version 1.3.2 (October 2017), zstd optionally implements very-long-range search and deduplication ( --long , 128 MiB window) similar to rzip or lrzip .
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 ...
In the implementation used for many games by Electronic Arts, [9] the size in bytes of a length–distance pair can be specified inside the first byte of the length–distance pair itself; depending on whether the first byte begins with a 0, 10, 110, or 111 (when read in big-endian bit orientation), the length of the entire length–distance ...
The reference implementation in C by Yann Collet is licensed under a BSD license. There are ports and bindings in various languages including Java, C#, Rust, and Python. [8] The Apache Hadoop system uses this algorithm for fast compression. LZ4 was also implemented natively in the Linux kernel 3.11. [9]
Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch.It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978.