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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".
Efficiency: By assigning shorter codes to frequently occurring symbols, Huffman coding reduces the average code length, resulting in efficient data representation and reduced storage requirements. Compatibility: Huffman coding is widely supported and can be seamlessly integrated into existing image compression standards and algorithms.
Zigzag ordering of JPEG image components. Entropy coding is a special form of lossless data compression. It involves arranging the image components in a "zigzag" order employing run-length encoding (RLE) algorithm that groups similar frequencies together, inserting length coding zeros, and then using Huffman coding on what is left.
More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies [(())] [ (())], where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to ...
Modified Huffman coding is used in fax machines to encode black-on-white images . It combines the variable-length codes of Huffman coding with the coding of repetitive data in run-length encoding . The basic Huffman coding provides a way to compress files with much repeating data, like a file containing text, where the alphabet letters are the ...
To avoid having excess code length over the entropy, one can use alphabet extension which codes blocks of symbols instead of coding individual symbols. This spreads out the excess coding length over many symbols. This is the “run” mode of JPEG-LS and it is executed once a flat or smooth context region characterized by zero gradients is ...
Adaptive coding refers to variants of entropy encoding methods of lossless data compression. They are particularly suited to streaming data , as they adapt to localized changes in the characteristics of the data, and don't require a first pass over the data to calculate a probability model.
The picture is an example of Huffman coding. Colors make it clearer, but they are not necessary to understand it (according to Wikipedia's guidelines): probability is shown in red, binary code is shown in blue inside a yellow frame. For a more detailed description see below (I couldn't insert a table here). Date: 18 May 2007: Source: self-made