05-compression-02-entropy coding.pptx - ICSY

More documents

Recommendations

Info

Huffman Coding Symbol Count Huffman p i E 135 00 0,2935 A 120 01 0,2609 D 110 10 0,2391 B 50 110 0,1087 C 45 111 0,0978 } Entropy: => H ≈ 2,1944 } Average code length: l = 2*p 1 +2*p 2 +2*p 3 +3*p 4 +3*p 5 ≈ 2,2065 Prof. Dr. Paul Müller, University of Kaiserslautern 12
Adaptive Huffman Coding } Problem - previous algorithm requires statistical knowledge (the probability distribution), often not available (e.g. live audio, video) - even when statistical knowledge is available, it could be too much overhead to send it } Solution - use of adaptive algorithms - here: Adaptive Huffman Coding - keeps up estimating the required probability distribution from previously encoded/decoded symbols by an update procedure Prof. Dr. Paul Müller, University of Kaiserslautern 13
Page 1 and 2: Entropy Coding } different probabil
Page 3 and 4: The Braille Prof. Dr. Paul Müller,
Page 5 and 6: Morse Code Example: Letter statisti
Page 7 and 8: Huffman Coding } Idea: Use short bi
Page 9 and 10: Huffman Coding Symbol Count P2 205
Page 11: Huffman Coding Symbol Count Huffman
Page 15 and 16: Adaptive Huffman Coding } Example n
Page 17 and 18: Adaptive Huffman Coding } A was inc
Page 19 and 20: Adaptive Huffman Coding } n+4-th Hu
Page 21 and 22: Huffman Coding Evaluation } Limitat
Page 23 and 24: Arithmetic Coding } arithmetic codi
Page 25 and 26: Arithmetic Coding } Example I - Fou
Page 27 and 28: Arithmetic Coding } Example I (cont
Page 29 and 30: Arithmetic Coding Example II (cont.
Page 31 and 32: Arithmetic Coding } Remarks - if th
Page 33 and 34: Lempel - Ziv (LZ77) } Algorithm for
Page 35 and 36: Lempel - Ziv (LZ77) } Remarks - the
Page 37 and 38: Lempel - Ziv - Welch (LZ78) } LZ78:

05-compression-02-entropy coding.pptx - ICSY

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?