Game Development Reference
In-Depth Information
⊡
⊣
⊤
⊦
16 11 10 16 24 40 51 61
12 12 14 19 26 58 60 55
14 13 16 24 40 57 69 56
14 17 22 29 51 87 80 62
18 22 37 56 68 109 103 77
24 35 55 64 81 104 113 92
49 64 78 87 103 121 120 101
72 92 95 98 112 100 103
Q
=
(1.1)
99
Entropy coding is a lossless compression technology, which maps the input sym-
bols (e.g., run-level coded coefficients) to a compressed bit stream. It achieves com-
pression by exploiting statistical redundancy of the input symbols, and representing
the high frequency symbols with shorter codewords and low frequency symbols with
longer codewords. Two of the most common entropy coding techniques are Huffman
coding (Huffman et al.
1952
) and arithmetic coding (Rissanen and Langdon
1979
).
Huffman coding designs sole codeword for each input symbol according to its occur-
rence frequency, which is stored in a look-up table. JPEG adopts Huffman coding as
its baseline entropy coding method. In video coding, another representative Huffman
coding method is context-based adaptive variable length coding (CAVLC) (Bjonte-
gaard and Lillevold
2002
;Au
2002
) in AVC/H.264, which defines multiple Huffman
tables according to the conditional probability of neighboring symbols. Arithmetic
coding is another kind of widely used entropy coding technique, which assigns a
codeword to the input symbol sequence instead of each symbol in Huffman coding.
Theoretically, arithmetic coding can represent a symbol with less than one bit on
average when the probability of the symbol is higher than 50%. A real successful
arithmetic coding scheme is proposed in AVC/H.264, named context-based adaptive
binary arithmetic coding (CABAC) (Marpe et al.
2003
). CABAC does not encode
the syntax elements directly, but only encodes each bin of every binarized syntax ele-
ments. The probability model is selected according to the previously encoded syntax
elements or bins, which are also updated with the value of the encoded symbols.
1.3 History of Video Coding Standard
There aremany organizations and companies that develop video coding tools for mas-
sive usage, some of them trying to make them into international standards, others
trying to make them into industry standards (Fig.
1.1
). There are different ways
we can divide them, such as technology-oriented, production-oriented, intelligence-
property-right-policy-oriented, and so on. Here, we want to categorize them into
three societies,
1. Ideal pure technology society, started 20-30 years ago, pays attention only to
integrating good technologies into standards, no matter how expensive the tech-
nology may cost later on. All ITU-T and ISO/IEC organizations belong to this
