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Efficient Huffman Decoding
Source: Proceedings International Conference on Image Processing, Volume: 1 , 2000, pp. 936–939 Author: Aggarwal, M.; Narayan, A. Speaker: Hsien-Wen Tseng Date: 11/15/2001
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Outline Introduction Lookup Table Method Proposed Algorithm Discussion
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Introduction Memory: O(2h) Complexity: O(h) Memory: O(n)
Complexity: a few computations K L I J H G F E D C B A
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Lookup Table Method
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Proposed Algorithm Huffman Table
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LMBC Function lmbc( ): The position of the first-bit-change. Example:
Decoding procedure: Determine the partition Search the codeword sequentially Example B =
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Canonical Huffman Code
Canonical codes are a subclass of Human codes, that have a numerical sequence property, i.e. codewords with the same length are binary representations of consecutive integers. The usage of canonical codes is simple decoding technique.
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Modified Huffman Table
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Decoding Algorithm Determine the partition
Using first bit and lmbc( ) function B = “ ”, LMBC = 3 Determine the common length Li and the numerically least codeword FCi in Pi Li = 7, FCi = “ ” Let C be the first Li bits of B, then (C-FCi) can be used as an index into lookup table yielding the desired symbol and its actual length li C = “ ”, C-FCi = 3, li = 5 The bitstream is left-shifted by li and process iterated until the last symbol
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Discussion The proposed algorithm requires very few computations to decode a codeword. The memory requirement would be large in worst case. Codewords {000100, } Require 24=16 entries In the MPEG-1, MPEG-2, H.261, H.263 standards, require additional memory only about one-third of n.
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