Abstract
This paper presents a masking effects based rate control scheme for high efficiency video coding (HEVC). Rate control is regarded as a very effective tool to improve the performance of video coding under the limited bandwidth. However, the state-of-the-art rate control algorithm based on Rš model ignores the characteristics of human visual system (HVS), which leads to poor performance in subjective quality. Moreover, some structural similarity (SSIM) or saliency based perceptual rate control algorithms only consider spatial characteristics. Since spatial and temporal visual masking effects can better reflect the characteristics of HVS, in this paper masking effects based perceptual factor for coding tree unit (CTU) is proposed, which takes both texture complexity and motion information into account. Then the proposed perceptual factor is utilized to guide bit allocation in CTU-level rate control. Experimental results show that the proposed scheme can effectively improve the coding performance compared with the R-š algorithm.
Li Song
Professor, IEEE Senior Member
Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.