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      SECTION 3.3                                                                    Filters



3.3.3 LZWDecode and FlateDecode Filters

      The LZWDecode and (in PDF 1.2) FlateDecode filters have much in common and
      are discussed together in this section. They decode data that has been encoded
      using the LZW or Flate data compression method, respectively:

      • LZW (Lempel-Ziv-Welch) is a variable-length, adaptive compression method
        that has been adopted as one of the standard compression methods in the Tag
        Image File Format (TIFF) standard. Details on LZW encoding follow in the
        next section.
      • The Flate method is based on the public-domain zlib/deflate compression
        method, which is a variable-length Lempel-Ziv adaptive compression method
        cascaded with adaptive Huffman coding. It is fully defined in Internet RFCs
        1950, ZLIB Compressed Data Format Specification, and 1951, DEFLATE Com-
        pressed Data Format Specification (see the Bibliography).

      Both of these methods compress either binary data or ASCII text but (like all
      compression methods) always produce binary data, even if the original data was
      text.

      The LZW and Flate compression methods can discover and exploit many
      patterns in the input data, whether the data is text or images. As described later,
      both filters support optional transformation by a predictor function, which
      improves the compression of sampled image data. Because of its cascaded
      adaptive Huffman coding, Flate-encoded output is usually much more compact
      than LZW-encoded output for the same input. Flate and LZW decoding speeds
      are comparable, but Flate encoding is considerably slower than LZW encoding.

      Usually, both Flate and LZW encodings compress their input substantially.
      However, in the worst case (in which no pair of adjacent characters appears
      twice), Flate encoding expands its input by no more than 11 bytes or a factor of
      1.003 (whichever is larger), plus the effects of algorithm tags added by PNG
      predictors. For LZW encoding, the best case (all zeros) provides a compression
      approaching 1365 : 1 for long files, but the worst-case expansion is at least a factor
      of 1.125, which can increase to nearly 1.5 in some implementations, plus the
      effects of PNG tags as with Flate encoding.

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