Context-based Adaptive Binary Arithmetic Coding (CA-BAC) is adopted as an entropy coding tool for main profile of the video coding standard H.264/AVC. CABAC achieves higher degree of redundancy reduction by estimating the conditional probability of each binary symbol which is the input to the arithmetic coder. This paper presents an entropy coding method based on CABAC. In the proposed method, the binary symbol is coded using more precisely estimated conditional probability, thereby leading to performance improvement. We apply our method to the standard and evaluate its performance for different video sources and various quantization parameters (QP). Experiment results show that our method outperforms the original CABAC in term of coding efficiency, and the average bit-rate savings are up to 1.2%.

In this paper, the statistical characteristic of the Error Detection Delay (EDD) of Finite Precision Binary Arithmetic Codes (FPBAC) is discussed. It is observed that, apart from the probability of the Forbidden Symbol (FS) inserted into the list of the source symbols, the probability of the source sequence and the operation precision as well as the position of the FS in the coding interval can affect the statistical characteristic of the EDD. Experiments demonstrate that the actual distribution of the EDD of FPBAC is quite different from the geometric distribution of infinite precision arithmetic codes. This phenomenon is researched deeply, and a new statistical model (gamma distribution) of the actual distribution of the EDD is proposed, which can make a more precise prediction of the EDD. Finally, the relation expressions between the parameters of gamma distribution and the related factors affecting the distribution are given.

Context-based adaptive binary arithmetic coding (CABAC) is the major entropy-coding algorithm employed in H.264/AVC. Although the performance gain of H.264/AVC is mainly due to CABAC, it is difficult to achieve a fast decoder because the decoding algorithm is basically sequential and computationally intensive. In this letter, a prediction scheme is proposed that enhances overall decoding performance by decoding two binary symbols at a time. A CABAC decoder based on the proposed prediction scheme improves the decoding performance by 24% compared to conventional decoders.

Secret information stored in a tamperfree device is revealed during the decryption or signature generation processes due to fault-based attack. In this paper, based on the coding approach, we propose a new fault-resistant system which enables any fault existing in modular multiplication and exponentiation computations to be detected with a very high probability. The proposed method can be used to implement all crypto-schemes whose basic operations are modular multiplications for resisting both memory and computational fault-based attacks with a very low computational overhead.