Improved Context-Based Adaptive Binary Arithmetic Coding in MPEG-4 AVC/H.264 Video Codec

Karwowski, Damian; Domański, Marek

doi:10.1007/978-3-642-15907-7_4

Cited by 6 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Step 1) Delete an average number of ones from the window (8) Step 2) Add a new symbol from the source (9) By combining (8) and (9), the final rule for recalculating the number of ones can be given as follows: (10) Equation (10) corresponds to the following probability estimation rule: (11) IV. STATE-OF-THE-ART ADAPTIVE BINARY ARITHMETIC CODER IMPLEMENTATIONS…”

Section: Probability Estimationmentioning

confidence: 99%

“…It is important to notice that if we define , then it is easy to see that the probability estimation rule (13) is based on rule (11).…”

Section: A Multiplication-free Implementation Based On State Machinementioning

confidence: 99%

“…The main disadvantage of this approach is that a multiplication operation is required. Improving of compression efficiency can be also achieved by modification of the context modeling in CABAC [11]- [13] but it also accompanied by significant increase of computation complexity.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Efficient Adaptive Binary Arithmetic Coder With Low Memory Requirement

Belyaev

Turlikov

Егиазарян

et al. 2013

IEEE J. Sel. Top. Signal Process.

View full text Add to dashboard Cite

In this paper we propose a novel efficient adaptive binary arithmetic coder which is multiplication-free and requires no look-up tables. To achieve this, we combine the probability estimation based on a virtual sliding window with the approximation of multiplication and the use of simple operations to calculate the next approximation after the encoding of each binary symbol. We show that in comparison with the M-coder the proposed algorithm provides comparable computational complexity, less memory footprint and bitrate savings from 0.5 to 2.3% on average for H.264/AVC standard and from 0.6 to 3.6% on average for HEVC standard.

show abstract

Section: Probability Estimationmentioning

confidence: 99%

“…It is important to notice that if we define , then it is easy to see that the probability estimation rule (13) is based on rule (11).…”

Section: A Multiplication-free Implementation Based On State Machinementioning

confidence: 99%

See 1 more Smart Citation

An Efficient Adaptive Binary Arithmetic Coder With Low Memory Requirement

Belyaev

Turlikov

Егиазарян

et al. 2013

IEEE J. Sel. Top. Signal Process.

View full text Add to dashboard Cite

show abstract

“…Additionally, they are concerned with the older versions of CABAC that found practical applications in coding technologies preceding VVC video technique (i.e., in H.264/MPEG-4 AVC [9] or H.265/MPEG-H HEVC). Numerous such works by the author can be mentioned here [20][21][22][23], in which the Context-Tree Weighting (CTW) method [24,25] was originally used to estimate the probabilities of data symbols more precisely. Recently, another idea of improving CABAC has also been proposed by the author [26].…”

Section: Bin Probability Estimation In Cabac -Other Literature Proposalsmentioning

confidence: 99%

Precise Probability Estimation of Symbols in VVC CABAC Entropy Encoder

Karwowski¹

2021

IEEE Access

Self Cite

View full text Add to dashboard Cite

The new version of the Context-based Adaptive Binary Arithmetic Coding (CABAC) that is used in the latest Versatile Video Coding (VVC) technology is the state-of-the-art in the field of entropy compression of video data. This paper gives an in-depth analysis of possible, further extensions of the CABAC technique for even more accurate estimation of the probabilities of coded data symbols. The paper considers four author's examples of such extensions. With respect to these examples, the paper shows the practical limitations of further increasing the efficiency of the newest version of CABAC used in VVC. Results show that for the considered methods of improvements the limit of gain in compression is up to 0.2073% on average, when compressing the VVC video data.INDEX TERMS probability estimation, entropy coding and arithmetic coding, VVC CABAC, video compression

show abstract

“…Several authors [3,4,5] have proposed to replace the simple CABAC data modeling by the more sophisticated Context-Tree Weighting (CTW), reporting about 1 to 3 % bit-rate savings for typical quality settings, at the cost of a significant increase in computational complexity, as reported in [5]. Belyaev et al [6] use a virtual sliding win-dow (VSW) for probability model estimation and report rate savings between 0.3 and 0.8 % for realistic quality settings.…”

Section: Introductionmentioning

confidence: 99%

Region-adaptive probability model selection for the arithmetic coding of video texture

Vermeirsch

Barbarien

Lambert

et al. 2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process moves into an area with different texture. To avoid this inefficiency, we propose to replace the probability models used in the original coder with multiple switchable sets of probability models. We determine the model set to use in each spatial region in an optimal manner, taking into account the additional signaling overhead. Experimental results show that this approach, when applied to H.264/AVC's context-based adaptive binary arithmetic coder (CABAC), yields significant bit-rate savings, which are comparable to or higher than those obtained using alternative improvements to CABAC previously proposed in the literature.

show abstract

Improved Context-Based Adaptive Binary Arithmetic Coding in MPEG-4 AVC/H.264 Video Codec

Cited by 6 publications

References 5 publications

An Efficient Adaptive Binary Arithmetic Coder With Low Memory Requirement

An Efficient Adaptive Binary Arithmetic Coder With Low Memory Requirement

Precise Probability Estimation of Symbols in VVC CABAC Entropy Encoder

Region-adaptive probability model selection for the arithmetic coding of video texture

Contact Info

Product

Resources

About