- Variable length encoding of symbols
- Exploit statistical frequency of symbols
- Efficient when symbol probabilities vary widely
- Use fewer bits to represent frequent symbols
- Use more bits to represent infrequent symbols
Features associated with Huffman Codes:
Huffman codes tend to be prefix-free binary code trees, consequently about all substantial factors apply appropriately.
Codes generated through the Huffman algorithm achieve the perfect code length up to the bit boundary. The maximum deviation is less than 1 bit.
Huffman Codes Example:
|Theoretical minimum: 2,176 bit|
|Code length Huffman : 2,226 bit|
The computation from the entropy results in an average code length of 2.176 bit per symbol on the assumption of the distribution mentioned. In contrast to this a Huffman code attains an average of 2.226 bits per symbol. Therefore Huffman coding methods the optimum on 97.74%.
An even better outcome is possible just using the arithmetic coding, however it's utilization is fixed through patents.