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  2. Run-length encoding - Wikipedia

    en.wikipedia.org/wiki/Run-length_encoding

    Run-length encoding (RLE) is a form of lossless data compression in which runs of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from ...

  3. Shannon coding - Wikipedia

    en.wikipedia.org/wiki/Shannon_coding

    In the field of data compression, Shannon coding, named after its creator, Claude Shannon, is a lossless data compression technique for constructing a prefix code based on a set of symbols and their probabilities (estimated or measured).

  4. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    This is the same as considering absolute entropy (corresponding to data compression) as a special case of relative entropy (corresponding to data differencing) with no initial data. The term differential compression is used to emphasize the data differencing connection.

  5. Arithmetic coding - Wikipedia

    en.wikipedia.org/wiki/Arithmetic_coding

    The process starts with the same interval used by the encoder: [0,1), and using the same model, dividing it into the same four sub-intervals that the encoder must have. The fraction 0.538 falls into the sub-interval for NEUTRAL, [0, 0.6); this indicates that the first symbol the encoder read must have been NEUTRAL, so this is the first symbol ...

  6. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...

  7. Shannon's source coding theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon's_source_coding...

    Source coding is a mapping from (a sequence of) symbols from an information source to a sequence of alphabet symbols (usually bits) such that the source symbols can be exactly recovered from the binary bits (lossless source coding) or recovered within some distortion (lossy source coding). This is one approach to data compression.

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