01-04-2012, 10:40 PM
Huffman encoding is a way to assign binary codes to symbols that reduces the overall number of bits used to encode a typical string of those symbols.
Huffman Code: Example
The following example bases on a data source using a set of five different symbols. The symbol's frequencies are:
Symbol Frequency
A 24
B 12
C 10
D 8
E 8
----> total 186 bit
(with 3 bit per code word)
The two rarest symbols 'E' and 'D' are connected first, followed by 'C' and 'D'. The new parent nodes have the frequency 16 and 22 respectively and are brought together in the next step. The resulting node and the remaining symbol 'A' are subordinated to the root node that is created in a final step.
Code Tree according to Huffman
Symbol Frequency Code Code total
Length Length
A 24 0 1 24
B 12 100 3 36
C 10 101 3 30
D 8 110 3 24
E 8 111 3 24
---------------------------------------
ges. 186 bit tot. 138 bit
(3 bit code)
Huffman Code: Example
The following example bases on a data source using a set of five different symbols. The symbol's frequencies are:
Symbol Frequency
A 24
B 12
C 10
D 8
E 8
----> total 186 bit
(with 3 bit per code word)
The two rarest symbols 'E' and 'D' are connected first, followed by 'C' and 'D'. The new parent nodes have the frequency 16 and 22 respectively and are brought together in the next step. The resulting node and the remaining symbol 'A' are subordinated to the root node that is created in a final step.
Code Tree according to Huffman
Symbol Frequency Code Code total
Length Length
A 24 0 1 24
B 12 100 3 36
C 10 101 3 30
D 8 110 3 24
E 8 111 3 24
---------------------------------------
ges. 186 bit tot. 138 bit
(3 bit code)
0300-9520262
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