Parametric model for context-based adaptive binary arithmetic coding
Huijuan Cui
Abstract
Huijuan Cui
Abstract
An adaptive binary arithmetic coding method was developed based on the context-based adaptive binary arithmetic coding(CABAC) entropy encoding method.A high efficiency parameter model and a low complexity parameter model were then developed for adaptive encoding with a change strategy based on a rate control mechanic.The low complexity parameter model uses 30% less computational time and 87.5% less memory than the high efficiency parameter model with almost the same reconstructed picture quality.This method provides a good tradeoff between the coding efficiency and the computational complexity of the CABAC entropy coding method.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
An adaptive binary arithmetic coding method was developed based on the context-based adaptive binary arithmetic coding(CABAC) entropy encoding method.A high efficiency parameter model and a low complexity parameter model were then developed for adaptive encoding with a change strategy based on a rate control mechanic.The low complexity parameter model uses 30% less computational time and 87.5% less memory than the high efficiency parameter model with almost the same reconstructed picture quality.This method provides a good tradeoff between the coding efficiency and the computational complexity of the CABAC entropy coding method.
Key concepts: Context-adaptive binary arithmetic coding, Arithmetic coding, Context-adaptive variable-length coding, Entropy encoding, Adaptive coding, Binary number, Coding (social sciences), Variable-length code