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  2. Lossless JPEG - Wikipedia

    en.wikipedia.org/wiki/Lossless_JPEG

    Adobe's DNG SDK provides a software library for encoding and decoding lossless JPEG with up to 16 bits per sample. ISO/IEC Joint Photography Experts Group maintains a reference software implementation which can encode both base JPEG (ISO/IEC 10918-1 and 18477-1) and JPEG XT extensions (ISO/IEC 18477 Parts 2 and 6-9), as well as JPEG-LS (ISO/IEC ...

  3. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    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".

  4. JPEG - Wikipedia

    en.wikipedia.org/wiki/JPEG

    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.

  5. Image compression - Wikipedia

    en.wikipedia.org/wiki/Image_compression

    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.

  6. Canonical Huffman code - Wikipedia

    en.wikipedia.org/wiki/Canonical_Huffman_code

    The normal Huffman coding algorithm assigns a variable length code to every symbol in the alphabet. More frequently used symbols will be assigned a shorter code. For example, suppose we have the following non-canonical codebook: A = 11 B = 0 C = 101 D = 100 Here the letter A has been assigned 2 bits, B has 1 bit, and C and D both have 3 bits.

  7. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    The adaptive encoding uses the probabilities from the previous sample in sound encoding, from the left and upper pixel in image encoding, and additionally from the previous frame in video encoding. In the wavelet transformation, the probabilities are also passed through the hierarchy. [3]

  8. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    For example, an image may have areas of color that do not change over several pixels; instead of coding "red pixel, red pixel, ..." the data may be encoded as "279 red pixels". This is a basic example of run-length encoding; there are many schemes to reduce file size by eliminating redundancy.

  9. Modified Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Modified_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 ...