Research On Entropy Coding In HEVC And Its Parallel Framework Design

High Efficiency Video Coding (HEVC) is a video compression format, a successor to H.264/AVC (Advanced Video Coding), that was jointly developed by the ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG). MPEG and VCEG established a Joint Collaborative Team on Video Coding (JCT-VC) to develop the HEVC standard. HEVC is said to double the data compression ratio compared to H.264/MPEG-4AVC at the same level of video quality. It can alternatively be used to provide substantially improved video quality at the same bit rate.HEVC uses a context-adaptive binary arithmetic coding (CABAC) algorithm that is fundamentally similar to CABAC in H.264/AVC. CABAC is the only entropy encoder method that is allowed in HEVC while there are two entropy encoder methods allowed by H.264/AVC, which are applied to the high profile and baseline encoding configuration respectively.The compression efficiency of HEVC improves at the expense of the increment of computational complexity. Currently HEVC is difficult to meet the requirements of real-time encoding. Due to its inherent serial nature, entropy coding has become the bottleneck of parallel processing for the overall video coding framework. Based on the analysis of the key technologies and encoding procedures of entropy coding in HEVC, this paper puts forward the corresponding entropy-coding optimization algorithms and entropy-coding parallel processing strategy.Firstly, this paper couducts a comprehensive analysis of the encoding process of entropy coding. The analysis finds that the computing methods in the current entropy coding framework need to be optimized and the whole process fails to consider the subjective characters of humans’eyes. Based on that, this paper proposes a binary arithmetic coding optimization algorithm and an entropy-bits estimation based perceptual rate-distortion optimization algorithm. Experiments show that the binary arithmetic coding optimization algorithm can improve the speed of entropy coding engine by3%to12%with a performance loss less than0.02%, while the subjective quality of the coded image in the rate-distortion optimization algorithm is much better when compared to the output of the HEVC official reference code.Secondly, considering that the whole entropy coding module in HEVC is highly serialized, this paper conducts a three-level analysis of the feasibility of parallel processing. Based on that, this paper realizes a parallel entropy-coding computing framework with multi-thread computing technology. Experimental results show that the computing speed of the parallel framework is65%to70%faster than that in the traditional serial architecture. Meanwhile, the subjective and objective quality of the coded image in the parallel framework is comparable to the output of the traditional method.