Entropy coding
Present by 陳群元
constraints
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Compression efficiency
Computational efficiency
Error robustness
Encoding
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DCT
Reordering
Run-level coding
Entropy coding
Encoding
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DCT
Reordering
Run-level coding
Entropy coding
DCT
Reordering
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The optimum method of reordering the quantised data
depends on the distribution of the non-zero coefficients.
Evenly distribution
Zigzag reordering pattern
Interlaced video-vary more in vertical
Modified reordering pattern
Encoding
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DCT
Reordering
Run-level coding
Entropy coding
Run-level coding
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Long sequences of identical values (zeros in this case) can
be represented as a (run, level) code
(run) indicates the number of zeros preceding a non-zero
value
(level) indicates the sign and magnitude of the non-zero
coefficient
Run-level coding(ex)
Encoding
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DCT
Reordering
Run-level coding
Entropy coding
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
True Huffman Coding
Generating the HufSman code tree
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1. Order the list of data in increasing order of probability.
2. Combine the two lowest-probability data items into a
‘node’ and assign the joint probability of the data items to
this node.
3. Reorder the remaining data items and node(s) in
increasing order of probability and repeat step 2.
encoding
decoding
disadvantage
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the decoder must use the same codeword set as the
encoder
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reduces compression efficiency.
calculating the probability table for a large video sequence
a significant computational overhead
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cannot be done until after the video data is encoded
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Table design
Final pair
Table design
H.263/MPEG-4 motion vector difference
(MVD)
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The H.263MPEG-4 differentially coded motion vectors
(MVD)
are each encoded as a pair of VLCs, one for the xcomponent and one for the y-component
mvd
mvd
H.26L universal VLC (UVLC)
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The emerging H.26L standard takes a step away from
individually calculated Huffman tables by using a ‘universal’
set of VLCs for any coded element. Each codeword is
generated from the following systematic list:
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Entropy Coding Example
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Variable Length Encoder Design
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Variable Length Decoder Design
Huffman Coding
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‘True’ Huffman Coding
Modified Huffman Coding
Table Design
Entropy Coding Example
Variable Length Encoder Design
Variable Length Decoder Design
Dealing with Errors
Dealing with Errors
Arithmetic Coding
Ex . encode (0,-1,0,2)
0.394
Ex . decode (0,-1,0,2)
Arithmetic coding vs huffman
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Ideal
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0.394 in this case, which can be represented as a fixedpoint number with sufficient accuracy using 9 bits
Huffman: 1;0011;1;0000110=>13 bits
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end
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