Since codes are added in a manner determined by the data, the decoder mimics building the table as it sees the resulting codes. Smart encoders can monitor the compression efficiency and clear the table whenever the existing table no longer matches the input well. The clear code lets the table be reinitialized after it fills up, which lets the encoding adapt to changing patterns in the input data. When the maximum code value is reached, encoding proceeds using the existing table, but new codes are not generated for addition to the table.įurther refinements include reserving a code to indicate that the code table should be cleared and restored to its initial state (a "clear code", typically the first value immediately after the values for the individual alphabet characters), and a code to indicate the end of data (a "stop code", typically one greater than the clear code). For such a reduced alphabet, the full 12-bit codes yielded poor compression unless the image was large, so the idea of a variable-width code was introduced: codes typically start one bit wider than the symbols being encoded, and as each code size is used up, the code width increases by 1 bit, up to some prescribed maximum (typically 12 bits). In an image based on a color table, for example, the natural character alphabet is the set of color table indexes, and in the 1980s, many images had small color tables (on the order of 16 colors). The idea was quickly adapted to other situations. The code for the sequence (without that character) is added to the output, and a new code (for the sequence with that character) is added to the dictionary. At each stage in compression, input bytes are gathered into a sequence until the next character would make a sequence with no code yet in the dictionary. 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. The scenario described by Welch's 1984 paper encodes sequences of 8-bit data as fixed-length 12-bit codes. It is the algorithm of the Unix file compression utility compress and is used in the GIF image format. The algorithm is simple to implement and has the potential for very high throughput in hardware implementations. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. Lempel–Ziv–Welch ( LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. ( August 2017) ( Learn how and when to remove this template message) Please help to improve this article by introducing more precise citations. This article includes a list of references, related reading, or external links, but its sources remain unclear because it lacks inline citations.
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