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  2. Run-length encoding - Wikipedia

    en.wikipedia.org/wiki/Run-length_encoding

    Even binary data files can be compressed with this method; file format specifications often dictate repeated bytes in files as padding space. However, newer compression methods such as DEFLATE often use LZ77-based algorithms, a generalization of run-length encoding that can take advantage of runs of strings of characters (such as BWWBWWBWWBWW).

  3. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:

  4. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy. The Lempel–Ziv (LZ) compression methods are among the most popular algorithms for lossless storage. [6] DEFLATE is a variation on LZ optimized for decompression speed and compression ratio, [7] but compression

  5. Bresenham's line algorithm - Wikipedia

    en.wikipedia.org/wiki/Bresenham's_line_algorithm

    (0,0) is at the top left corner of the grid, (1,1) is at the top left end of the line and (11, 5) is at the bottom right end of the line. The following conventions will be applied: the top-left is (0,0) such that pixel coordinates increase in the right and down directions (e.g. that the pixel at (7,4) is directly above the pixel at (7,5)), and

  6. Lempel–Ziv–Welch - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Welch

    The scenario described by Welch's 1984 paper [1] encodes sequences of 8-bit data as fixed-length 12-bit codes. The codes from 0 to 255 represent 1-character sequences consisting of the corresponding 8-bit character, and the codes 256 through 4095 are created in a dictionary for sequences encountered in the data as it is encoded.

  7. Lempel–Ziv–Markov chain algorithm - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Markov_chain...

    40 indicates a 4 GB − 1 dictionary size; Even values less than 40 indicate a 2 v/2 + 12 bytes dictionary size; Odd values less than 40 indicate a 3×2 (v − 1)/2 + 11 bytes dictionary size; Values higher than 40 are invalid; LZMA2 data consists of packets starting with a control byte, with the following values: 0 denotes the end of the file

  8. UTF-16 - Wikipedia

    en.wikipedia.org/wiki/UTF-16

    The Joliet file system, used in CD-ROM media, encodes file names using UCS-2BE (up to sixty-four Unicode characters per file name). Python version 2.0 officially only used UCS-2 internally, but the UTF-8 decoder to "Unicode" produced correct UTF-16. There was also the ability to compile Python so that it used UTF-32 internally, this was ...

  9. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.