The B-coder: an improved binary arithmetic coder and probability estimator

In this paper we present the B-coder, an efficient binary arithmetic coder that performs extremely well on a wide range of data. The B-coder should be classed as an `approximate’ arithmetic coder, because of its use of an approximation to multiplication. We show that the approximation used in the B-coder has an efficiency cost of 0.003 compared to Shannon entropy. At the heart of the B-coder is an efficient state machine that adapts rapidly to the data to be coded. The adaptation is achieved by allowing a fixed table of transitions and probabilities to change within a given tolerance. The combination of the two techniques gives a coder that out-performs the current state-of-the-art binary arithmetic coders

The B-coder: an improved binary arithmetic coder and probability estimator

In this paper we present the B-coder, an efficient binary arithmetic coder that performs extremely well on a wide range of data. The B-coder should be classed as an `approximate’ arithmetic coder, because of its use of an approximation to multiplication. We show that the approximation used in the B-coder has an efficiency cost of 0.003 compared to Shannon entropy. At the heart of the B-coder is an efficient state machine that adapts rapidly to the data to be coded. The adaptation is achieved by allowing a fixed table of transitions and probabilities to change within a given tolerance. The combination of the two techniques gives a coder that out-performs the current state-of-the-art binary arithmetic coders

Design and application of variable-to-variable length codes

This work addresses the design of minimum redundancy variable-to-variable length (V2V) codes and studies their suitability for using them in the probability interval partitioning entropy (PIPE) coding concept as an alternative to binary arithmetic coding. Several properties and new concepts for V2V codes are discussed and a polynomial-based principle for designing V2V codes is proposed. Various minimum redundancy V2V codes are derived and combined with the PIPE coding concept. Their redundancy is compared to the binary arithmetic coder of the video compression standard H.265/HEVC

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

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