Why does LZ77 DEFLATE use Huffman encoding for it's second pass instead of LZW? Is there something about their combination that is optimal? If so, what is the nature of the output of LZ77 that makes it more suitable for Huffman compression than LZW or some other method entirely?
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2 Answers
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LZW tries to take advantage of repeated strings, just like the first "stage" as you call it of LZ77. It then does a poor job of entropy coding that information. LZW has been completely supplanted by more modern approaches. (Except for its legacy use in the GIF format.) Once LZ77 generates a list of literals and matches, there is nothing left for LZW to take advantage of, and it would then make an almost completely ineffective entropy coder for that information.
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Mark Adler could best answer this question.
The details of how the LZ77 and Huffman work together need some closer examination. Once the raw data has been turned into a string of characters and special length, distance pairs, these elements must be represented with Huffman codes.
Though this is NOT, repeat, NOT standard terminology, call the point where we start reading in bits a "dial tone." After all, in our analogy, the dial tone is where you can start specifying a series of numbers that will end up mapping to a specific phone. So call the very beginning a "dial tone." At that dial tone, one of three things could follow: a character, a length-distance pair, or the end of the block. Since we must be able to tell which it is, all the possible characters ("literals"), elements that indicate ranges of possible lengths ("lengths"), and a special end-of-block indicator are all merged into a single alphabet. That alphabet then becomes the basis of a Huffman tree. Distances don't need to be included in this alphabet, since they can only appear directly after lengths. Once the literal has been decoded, or the length-distance pair decoded, we are at another "dial-tone" point and we start reading again. If we got the end-of-block symbol, of course, we're either at the beginning of another block or at the end of the compressed data.
Length codes or distance codes may actually be a code that represents a base value, followed by extra bits that form an integer to be added to the base value.
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Long story short. LZ77 provides duplicate elimination. Huffman coding provides bit reduction. It's also on the wiki.
