High dynamic range (HDR) video compression technology, which is capable of delivering a wider range of luminance and a larger colour gamut than standard dynamic range (SDR) technology, has been widely used in recent years in many fields, including industrial image processing, digital entertainment, and machine vision. Rate control (RC) is of paramount importance to HDR compression and transmission; accordingly, an RC scheme for HDR in High Efficiency Video Coding (HEVC) is proposed in this paper. First, considering the HDR characteristics, we propose an HDR-Visual Difference Predictor (VDP)-2-based ratedistortion (R-D) model to improve the coding performance. Second, we directly utilize λ rather than the bit rate in the optimization process to obtain the optimal solution. Finally, we propose a new model parameter estimation method to further reduce the RC errors. According to our experimental results, significant bit rate reductions in terms of HDR-VDP-2, the Video Quality Metric (VQM) and the mean peak-signal-to-noise ratio (mPSNR) can be achieved on average compared with the stateof-the-art algorithm used in HM16.19.
|Journal||IEEE Transactions on Circuits and Systems for Video Technology|
|Early online date||16 Dec 2019|
|Publication status||Published - Dec 2020|
Bibliographical noteThis work was supported in part by the Hong Kong Innovation and Technology Fund University-Industry Collaboration Programme (ITF UICP) under Grant 9440174, in part by the Natural Science Foundation of China under Grant 61801303 and Grant 61672443, in part by the Hong Kong Research Grants Council (RGC) General Research Fund under Grant 9042489 and Grant CityU 11206317, in part by the Hong Kong Research Grants Council (RGC) General Research Fund under Grant 9042322 and Grant CityU 11200116, in part by the Hong Kong Research Grants Council (RGC) Early Career Scheme under Grant 9048122 and Grant CityU 21211018, in part by the City University of Hong Kong under Grant 7200539/CS, in part by the Start Up Project of Chongqing University under Grant 02160011044118, in part by the Natural Science Foundation of China under Grant 61876026, in part by the Research on Key Technologies of Pedestrian Recognition for Different Resolution under Grant qnsy2018006, in part by the Research on Key Technologies of Pedestrian Recognition in Complex Scenes under Grant CST_2019SN02, in part by the Research on Pedestrian Recognition for Monitoring through the Qiannan Kehe Discipline Construction under Grant Zi (2018) No.7, in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LQ20F020006, and in part by the Scientific Research Fund of Zhejiang Provincial Education Department under Grant Y201941813.
- global optimization
- rate control