Among the existing video-related applications, a large proportion have requirements for the scalability of the video coding complexity, such as live video chatting and video coding on power-limited mobile devices. Hence, the complexity control algorithms, which aim to make an effective and flexible tradeoff between coding complexity and rate-distortion (RD) performance, have a great practical value. In this paper, a novel complexity control scheme for high efficiency video coding (HEVC) is proposed by dynamically adjusting the depth range for each coding tree unit (CTU). To control the complexity accurately, a statistical model is proposed to estimate the coding complexity of each CTU. Then the complexity budget is allocated to each CTU proportionally to its estimated complexity. At last, the depth range is optimized for each CTU based on the allocated complexity and the probability that contains the actual maximum depth. Our method works well even if the ratio of target complexity to full complexity drops to 40%. The experimental results show that our proposed method outperforms other four state-of-the-art methods in terms of the RD performance, and has superior complexity control accuracy and complexity control stability compared with other one-pass complexity control strategies.
Bibliographical noteThis work was supported in part by the Natural Science Foundation of China under Grant 61672443 and in part by Hong Kong RGC General Research Fund 9042322 (CityU 11200116).
- Coding tree unit (CTU)
- Complexity allocation
- Complexity control
- High efficiency video coding (HEVC).