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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".
Lossless JPEG is a 1993 addition to JPEG standard by the Joint Photographic Experts Group to enable lossless compression. However, the term may also be used to refer to all lossless compression schemes developed by the group, including JPEG 2000, JPEG-LS, and JPEG XL . Lossless JPEG was developed as a late addition to JPEG in 1993, using a ...
The JPEG standard also allows, but does not require, decoders to support the use of arithmetic coding, which is mathematically superior to Huffman coding. However, this feature has rarely been used, as it was historically covered by patents requiring royalty-bearing licenses, and because it is slower to encode and decode compared to Huffman coding.
In image compression, Huffman coding is typically applied after other transformations like Discrete Cosine Transform (DCT) in the case of JPEG compression. After transforming the image data into a frequency domain representation, Huffman coding is used to encode the transformed coefficients efficiently.
In order for a symbol code scheme such as the Huffman code to be decompressed, the same model that the encoding algorithm used to compress the source data must be provided to the decoding algorithm so that it can use it to decompress the encoded data. In standard Huffman coding this model takes the form of a tree of variable-length codes, with ...
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. [ 1] By contrast, lossy compression permits reconstruction only of an approximation ...
optimisation of the Huffman coding layer of a JPEG file to increase compression, conversion between progressive and sequential JPEG formats, conversion between Huffman and arithmetic coding in the entropy coding layer. [5] [6] [7] These transformations are each completely lossless and reversible. The transformations on the image data comprise:
Arithmetic coding. Arithmetic coding ( AC) is a form of entropy encoding used in lossless data compression. Normally, a string of characters is represented using a fixed number of bits per character, as in the ASCII code. When a string is converted to arithmetic encoding, frequently used characters will be stored with fewer bits and not-so ...