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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".
To spot matches, the encoder must keep track of some amount of the most recent data, such as the last 2 KB, 4 KB, or 32 KB. The structure in which this data is held is called a sliding window, which is why LZ77 is sometimes called sliding-window compression. The encoder needs to keep this data to look for matches, and the decoder needs to keep ...
The standard way to represent a signal made of 4 symbols is by using 2 bits/symbol, but the entropy of the source is 1.73 bits/symbol. If this Huffman code is used to represent the signal, then the entropy is lowered to 1.83 bits/symbol; it is still far from the theoretical limit because the probabilities of the symbols are different from negative powers of two.
Snappy (previously known as Zippy) is a fast data compression and decompression library written in C++ by Google based on ideas from LZ77 and open-sourced in 2011. [3] [4] It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression.
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.
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.
Typically, compressions using lossless operation mode can achieve around 2:1 compression ratio for color images. [5] This mode is quite popular in the medical imaging field, and defined as an option in DNG standard, but otherwise it is not very widely used because of complexity of doing arithmetics on 10, 12, or 14bpp values on typical embedded 32-bit processor and a little resulting gain in ...
Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding. It permits building the code as the symbols are being transmitted, having no initial knowledge of source distribution, that allows one-pass encoding and adaptation to changing conditions in data.