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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".
The optimal length-limited Huffman code will encode symbol i with a bit string of length h i. The canonical Huffman code can easily be constructed by a simple bottom-up greedy method, given that the h i are known, and this can be the basis for fast data compression. [2]
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 ]
Lempel–Ziv–Stac (LZS, or Stac compression or Stacker compression [1]) is a lossless data compression algorithm that uses a combination of the LZ77 sliding-window compression algorithm and fixed Huffman coding.
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 ...
Unlike variable-length codes, which include Huffman and Lempel–Ziv coding, Tunstall coding is a code which maps source symbols to a fixed number of bits. [2]Both Tunstall codes and Lempel–Ziv codes represent variable-length words by fixed-length codes.
Huffyuv (or HuffYUV) is a lossless video codec created by Ben Rudiak-Gould which is meant to replace uncompressed YCbCr as a video capture format. The codec can also compress in the RGB color space. "Lossless" means that the output from the decompressor is bit-for-bit identical with the original input to the compressor.
Compression ratios are around 50–60% of the original size, [49] which is similar to those for generic lossless data compression. Lossless codecs use curve fitting or linear prediction as a basis for estimating the signal. Parameters describing the estimation and the difference between the estimation and the actual signal are coded separately.
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