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Source coding

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الكلية كلية الهندسة     القسم  الهندسة الكهربائية     المرحلة 4
أستاذ المادة ابراهيم عبد الله مرداس الشجيري       6/8/2011 3:57:49 PM

Huffman Coding

 

 

 

1.    Sort the source alphabet in order of decreasing probability. These are the leaves of the “coding tree.”

 

 

 

2.    Merge the r source symbols with smallest probability into a new “source symbol” with probability equal to the sum of the r smallest    probabilities. This is an interior node of the coding tree.

 

 

 

3.    Repeat this process until only one source symbol (with probability one) remains. This is the root of the coding tree. Huffman Coding (contd.)

 

 

 

4.    To find the codeword for a given source symbol trace the coding tree from the root to the source symbol (leaf), e.g., when r = 2, add a zero to the codeword when traversing a left branch and a one when traversing a right branch.

 

 

 

 

 

·       If the number of symbols in the code alphabet is r, then there must be  n = r+k(r?1) source alphabet symbols (k integer) in the Huffman code.

 

 

 

·       This is because each stage of the Huffman coding algorithm reduces the size of the source alphabet by r?1 and there must be r symbols in the final stage to merge to form the root of the coding tree.

 

 

 

·       If there are less source alphabet symbols, then one must add source symbols (with probability zero), until n= r+k(r?1) for some integer k.

 

 

 

 

 

 

 

 

 
 
 

Huffman coding example.

 

 


Fano Coding

 

1. Merge the source symbols into r sets, so that the sums of the probabilities

     in each set are as equal as possible.

 

2. Assign a unique code alphabet symbol to the members of each set.

 

3. Repeat this process until the sets are of size r or less.

 

 

 

Fano Coding example


 

Fixed-length source codes

The simplest approach to encoding a discrete source into binary digits is to convert each source letter individually into a fixed-length block of L bits. There are (2L)different combinations of values for a block of L bits. Thus, if the number of letters in the source alphabet, M = |X |, satisfies M  2L, then a different binary L-tuple may be assigned to each letter. Thus the letters can be uniquely decoded from the binary blocks, and the code is uniquely decodable.

 

For example, if the alphabet X consists of the M = 7 letters {a; b; c; d; e; f; g}, then binary blocks of length 3 are sufficient, and there exists an invertible mapping from X to a subset of 7 binary 3-tuples; e.g.,

 

 

 


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