Context-based Adaptive Binary Arithmetic Coding (CABAC) is the entropy coding module in the HEVC/H video coding standard. As in its predecessor. High Throughput CABAC Entropy Coding in HEVC. Abstract: Context-adaptive binary arithmetic coding (CAB-AC) is a method of entropy coding first introduced . Context-based Adaptive Binary Arithmetic Coding (CABAC) is a method of entropy coding which is widely used in the next generation standard of video coding.

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On the lower level, there is the quantization-parameter dependent initialization, which is invoked at the beginning of each slice. In general, a binarization scheme defines a unique mapping of syntax element values to sequences of binary decisions, so-called bins, which can also be interpreted in terms of a binary code tree.

CABAC is also difficult to parallelize and vectorize, so other forms of parallelism such czbac spatial region parallelism may be coupled with its use.

Context-adaptive binary arithmetic coding – Wikipedia

The definition of the decoding process is designed to facilitate low-complexity implementations of arithmetic encoding and decoding. The design of CABAC involves the key elements of binarization, cagac modeling, and binary arithmetic coding.

It has three distinct properties:. If e k is small, then there is a high probability that the current MVD will have a small magnitude; conversely, if e k is large then it is more likely that the current MVD will have a large magnitude.

The design of these four prototypes is based on a priori knowledge about the typical characteristics of the source data to be modeled and it reflects the aim to find a good compromise between the conflicting objectives of avoiding unnecessary modeling-cost overhead and exploiting the statistical dependencies to a large extent.

Choose a context model for each bin. Note however that the actual transition rules, as tabulated in CABAC and as shown in the graph above, were determined to be only approximately equal to those derived by this exponential aging rule.

It generates an initial state cahac depending on the given slice-dependent quantization parameter SliceQP using a pair of so-called initialization parameters for each model which describes a modeled linear relationship between the SliceQP and the model probability p. This page was last edited on 14 Novemberat Retrieved from ” https: Video Coding for Next-generation Multimedia.

Usually the addition of syntax elements also affects the distribution of already available syntax elements which, in general, for a VLC-based entropy-coding approach jevc require to cabav the VLC tables of the given syntax elements rather than just adding a suitable VLC code for the new syntax element s. Pre-Coding of Transform-Coefficient Levels Coding of residual data in CABAC involves specifically designed syntax elements that are different from those used in the traditional run-length pre-coding approach.


On the lowest level of processing in CABAC, each bin value enters the binary arithmetic encoder, either in regular or bypass coding mode. We select a probability table context model accordingly. As an extension of this low-level pre-adaptation of probability models, CABAC provides two additional pairs of initialization parameters cabbac each model that is used in predictive P or bi-predictive B slices.

The design of CABAC has been highly inspired by our prior work on wavelet-based image and video coding. For the latter, a fast branch of the coding engine with a considerably reduced complexity is used while for the former coding mode, encoding of the given bin value depends on the actual state of the associated adaptive probability model that is passed along with the bin value to the M coder – a term that has been chosen for the novel table-based binary arithmetic coding engine in CABAC.

It first converts all non- binary symbols to binary. The latter is chosen for bins related to the sign information or for lower significant bins, which are assumed to be uniformly distributed hhevc for which, consequently, the whole regular binary arithmetic encoding process is simply bypassed.

One of 3 models is selected for bin 1, based on previous coded MVD values. In the following, we will present some important aspects of probability estimation in CABAC that are not intimately tied to the M coder design. From that time until completion of the first standard specification ehvc H. Support of additional coding cxbac such as interlaced coding, variable-block size transforms as considered for Version 1 of H.

At that time – and also at a later stage when the scalable extension of H. For each hefc with at least one nonzero quantized transform coefficient, a sequence of binary significance flags, indicating the position of significant i.

In this way, CABAC enables selective context modeling on a sub-symbol level, and hence, provides an efficient hevvc for exploiting inter-symbol redundancies at significantly reduced overall modeling or learning costs.

These aspects are mostly related ccabac implementation complexity and additional requirements in terms of conformity and applicability.

Probability estimation in CABAC is based on a table-driven estimator using a finite-state machine FSM approach with tabulated transition rules heevc illustrated above. From Wikipedia, the free encyclopedia.

Utilizing suitable context models, a given inter-symbol redundancy can be exploited by switching between different probability models according to already-coded symbols in the neighborhood of the current symbol to encode.

Update cabzc context models. Probability Estimation and Binary Arithmetic Coding On the lowest level of processing in CABAC, each bin value enters the binary arithmetic encoder, either in regular or bypass coding mode. CABAC is based on arithmetic codingwith a cbaac innovations and changes to adapt it to the needs of video encoding standards: This is the purpose of the initialization process for context models in CABAC, which operates on two levels. Nevc with these significance flags, a sequence of so-called last flags one for each significant coefficient level is generated for signaling the position of the last significant level within the scanning path.


CABAC has multiple probability modes for different contexts.

Context-Based Adaptive Binary Arithmetic Coding (CABAC) – Fraunhofer Heinrich Hertz Institute

For the specific choice of context models, four basic design types are employed in CABAC, where two of them, as further described below, are applied to coding of transform-coefficient levels, only. The other method specified in H. The selected context model supplies two probability estimates: These estimates determine the two sub-ranges that the arithmetic coder uses to encode the bin. As an important design decision, the latter case is generally applied to the cabbac frequently observed bins only, whereas the other, usually less frequently observed bins, will be hec using a joint, typically zero-order probability model.

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Context-adaptive binary arithmetic coding

The L1 norm of two previously-coded values, e kis calculated:. Each probability model in CABAC can take one out of different states with associated probability uevc p ranging in the interval [0.

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The specific features and the underlying design principles of the M coder can be found here. Arithmetic coding is finally applied to compress the data. Circuits and Systems for Video TechnologyVol. The design of binarization schemes in CABAC is based on a few elementary prototypes whose structure enables simple online calculation and which are adapted to some suitable model-probability distributions.

This allows the discrimination of statistically different sources with the result of a significantly better adaptation to the individual statistical characteristics. In the regular coding mode, each bin value is encoded by using the regular binary arithmetic-coding engine, where the associated probability model is either determined by a fixed choice, without any context modeling, or adaptively chosen depending on the related context model.

This so-called significance information is transmitted as a preamble of the regarded transform block followed by the magnitude and sign information of nonzero levels in reverse scanning order. The arithmetic decoder is described in some detail in the Standard.