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Download as PDF; Printable version; ... and Python. [8] ... LZ4 is a lossless data compression algorithm that is focused on compression and decompression speed.
The "trick" that allows lossless compression algorithms, used on the type of data they were designed for, to consistently compress such files to a shorter form is that the files the algorithms are designed to act on all have some form of easily modeled redundancy that the algorithm is designed to remove, and thus belong to the subset of files ...
This algorithm uses a dictionary compression scheme somewhat similar to the LZ77 algorithm published by Abraham Lempel and Jacob Ziv in 1977 and features a high compression ratio (generally higher than bzip2) [2] [3] and a variable compression-dictionary size (up to 4 GB), [4] while still maintaining decompression speed similar to other ...
LZ77 algorithms achieve compression by replacing repeated occurrences of data with references to a single copy of that data existing earlier in the uncompressed data stream. A match is encoded by a pair of numbers called a length-distance pair , which is equivalent to the statement "each of the next length characters is equal to the characters ...
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 ...
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.
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".
Allows the user to adjust the balance between compression ratio and compression speed, without affecting the speed of decompression; LZO supports overlapping compression and in-place decompression. As a block compression algorithm, it compresses and decompresses blocks of data. Block size must be the same for compression and decompression.