A Study of Complexity Control of High EfficiencyVideo Coding (HEVC) Encoder

• Main Authors: Jyun-Liang Li, 李俊良
• Other Authors: Chou-Chen Wang
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/24329762154636901842

碩士 === 義守大學 === 電子工程學系 === 101 === With the rapid development of multimedia technology and hardware, the video of 4K2K (or 8K4K) high-resolution will become the main specification of large size digital TV in future. Therefore, the Joint Collaborative Team on Video Coding (JCT-VC) has been developed a newest high efficiency video coding (HEVC) to satisfy the high-resolution requirement in January 2013. HEVC can achieve 50% bit rate reduction in comparison with H.264 High Profile, this is because the HEVC adopts some new coding quad-tree structures including coding unit (CU), prediction unit (PU) and transform unit (TU). The CU size ranges from largest CU (64×64) to the smallest CU (8×8) pixels and TUs vary from 32×32 to 4×4 pixels, and seven inter-partition modes are used for the PUs. The rate distortion (RD) cost under all partition modes and all CU sizes has to be calculated so that the optimal CU size and partition mode can be selected. However, this “try all and select the best” method will result in the high computational complexity and limit the use of HEVC encoders in real-time applications. The complexity of HEVC encoder is too high to satisfy the real-time video applications. Therefore, a complexity control for HEVC is critical issue to run on bandwidth limited environment and power-constrained devices. To overcome the problem of high encoding complexity, there have been many fast encoding methods proposed to reduce the computation load of HEVC. Recently, Correa et al. proposed a novel complexity control algorithm (CCA) for HEVC [2]. The CCA predicts the encoding complexity of next frame by using the maximum CU depth (MaxCUD) map of previous coded frame, and define the combination of frames to encode. However, CCA can’t effectively achieve complexity control of HEVC for the lower encoding time-constrained requirement due to the lack of flexibility. In order to further improve the performance of CCA, we propose a modified CCA (MCCA) by exploiting the characteristics of high temporal-spatial correlation exists in nature video sequences. In this thesis, we predict the encoding complexity of next frame by using the best CU tree (BestCUT) map of previous coded frame, and adopt more flexible complexity control method. The simulation results show that the proposed MCCA can achieve an average time improving ratio (TIR) about 74.85% as compared to HEVC (HM8.1). Compared with the CCA [2], the proposed MCCA can further achieve an average TIR about 26.5%. In addition, MCCA can successfully achieve video coding under lower predefined time target, however, HM8.1 and CCA are all fail to encode for the same time-constrained condition.