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LZWL
LZWL is a syllable-based variant of the LZW (Lempel-Ziv-Welch) compression algorithm, designed to work with syllables derived from any syllable decomposition algorithm. This approach allows LZWL to efficiently process both syllables and words, offering a nuanced method for data compression. Algorithm The LZWL algorithm initializes by populating a dictionary with all characters from the alphabet. It then searches for the longest string, S, that exists in both the dictionary and as a prefix of the unencoded portion of the input. The algorithm outputs the identifier of S and augments the dictionary with a new phrase, which combines S with the subsequent character in the input. The input position advances by the length of S. During decoding, LZWL addresses scenarios where the received phrase identifier does not exist in the dictionary by constructing the missing phrase from the concatenation of the last added phrase and its initial character. Syllable-Based Adaptation In its syllable ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lempel–Ziv–Welch
Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. The algorithm is simple to implement and has the potential for very high throughput in hardware implementations. It is the algorithm of the widely used Unix file compression utility compress and is used in the GIF image format. Algorithm The scenario described by Welch's 1984 paper 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. 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 co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding; encoding done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a signal. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
