1. 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

2. Outline
Introduction
Lookup Table Method
Proposed Algorithm
Discussion

3. 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

4. Lookup Table Method

5. Proposed Algorithm Huffman Table

6. LMBC Function lmbc( ): The position of the first-bit-change. Example:
Decoding procedure:
Determine the partition
Search the codeword sequentially
Example
B =

7. 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.

8. Modified Huffman Table

9. 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

10. 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.