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Two-Stage Perceptual Quality Oriented Rate Control Algorithm for HEVC

Published: 22 January 2024 Publication History
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  • Abstract

    As a practical technique in mainstream video coding applications, rate control dominates important to ensure compression quality with limited bitrates constraints. However, most rate control methods mainly focus on objective quality while ignoring the perceptual quality improvement for human eyes. In this paper, we propose a two-stage rate control algorithm to optimize the perceptual quality at the frame encoding stage and the coding tree unit (CTU) encoding stage for high efficiency video coding (HEVC), respectively. Firstly, for the frame encoding stage, with inter-frame distortion dependency consideration, a frame-level rate control method is presented by adjusting the frame-level Lagrange multiplier adaptively with a preprocessing method. Secondly, for the CTU encoding stage, we propose a saliency-based CTU-level perceptual quality rate control algorithm, which employs CTU-level saliency weight to adjust the perceptual rate-distortion (R-D) model. We conduct the CTU-level rate control by an optimized Lagrange multiplier and quantization parameter (QP) to achieve perceptual quality optimization. Extensive experimental results reveal that, compared with state-of-the-art rate control methods on HEVC, our algorithm achieves significant perceptual coding performance with improved subjective visual quality.

    References

    [1]
    Frank Bossen et al. 2013. Common test conditions and software reference configurations. JCTVC-L1100 12 (2013), 7.
    [2]
    Benjamin Bross, Ye-Kui Wang, Yan Ye, Shan Liu, Jianle Chen, Gary J. Sullivan, and Jens-Rainer Ohm. 2021. Overview of the versatile video coding (VVC) standard and its applications. IEEE Transactions on Circuits and Systems for Video Technology 31, 10 (2021), 3736–3764.
    [3]
    Zhenzhong Chen and Xiang Pan. 2019. An optimized rate control for low-delay H. 265/HEVC. IEEE Transactions on Image Processing 28, 9 (2019), 4541–4552.
    [4]
    Hyomin Choi, Junghak Nam, Jonghun Yoo, D. Sim, and I. V. Bajic. 2012. Rate control based on unified RQ model for HEVC. ITU-T SG16 Contribution, JCTVC-H0213 (2012), 1–13.
    [5]
    Fabio De Vito, Tanir Ozcelebi, Reha Civanlar, A. Murat Tekalp, and Juan Carlos De Martin. 2005. Rate control for GOP-level rate adaptation in H. 264 video coding. In Proceedings of VLBV Workshop.
    [6]
    Wei Gao, Sam Kwong, Hui Yuan, and Xu Wang. 2015. DCT coefficient distribution modeling and quality dependency analysis based frame-level bit allocation for HEVC. IEEE Transactions on Circuits and Systems for Video Technology 26, 1 (2015), 139–153.
    [7]
    Wei Gao, Sam Kwong, Yu Zhou, and Hui Yuan. 2016. SSIM-based game theory approach for rate-distortion optimized intra frame CTU-level bit allocation. IEEE Transactions on Multimedia 18, 6 (2016), 988–999.
    [8]
    Yanchao Gong, Shuai Wan, Kaifang Yang, Hong Ren Wu, and Ying Liu. 2017. Temporal-layer-motivated lambda domain picture level rate control for random-access configuration in H. 265/HEVC. IEEE Transactions on Circuits and Systems for Video Technology 29, 1 (2017), 156–170.
    [9]
    Hongwei Guo, Ce Zhu, Shengxi Li, and Yanbo Gao. 2018. Optimal bit allocation at frame level for rate control in HEVC. IEEE Transactions on Broadcasting 65, 2 (2018), 270–281.
    [10]
    Hongwei Guo, Ce Zhu, Mai Xu, and Shuai Li. 2019. Inter-block dependency-based CTU level rate control for HEVC. IEEE Transactions on Broadcasting 66, 1 (2019), 113–126.
    [11]
    Xiaofeng Huang, Weihong Niu, Qiuyang Zhang, Haibing Yin, Guoqing Xiang, Shanshe Wang, and Siwei Ma. 2023. Rate-distortion optimization-based learned fractional interpolation filter design for HEVC. IEEE Transactions on Broadcasting 69, 2 (2023), 422–435. DOI:
    [12]
    Sehwan Ki, Sung-Ho Bae, Munchurl Kim, and Hyunsuk Ko. 2018. Learning-based just-noticeable-quantization-distortion modeling for perceptual video coding. IEEE Transactions on Image Processing 27, 7 (2018), 3178–3193.
    [13]
    Jaeil Kim, Sung-Ho Bae, and Munchurl Kim. 2015. An HEVC-compliant perceptual video coding scheme based on JND models for variable block-sized transform kernels. IEEE Transactions on Circuits and Systems for Video Technology 25, 11 (2015), 1786–1800.
    [14]
    ChungWen Ku, Guoqing Xiang, Feng Qi, Wei Yan, Yuan Li, and Xiaodong Xie. 2019. Bit allocation based on visual saliency in HEVC. In 2019 IEEE Visual Communications and Image Processing (VCIP ’19). IEEE, 1–4.
    [15]
    B. Lee, M. Kim, and T. Q. Nguyen. 2013. A frame-level rate control scheme based on texture and nontexture rate models for high efficiency video coding. IEEE Transactions on Circuits and Systems for Video Technology 24, 3 (2013), 465–479.
    [16]
    Bin Li, Houqiang Li, Li Li, and Jinlei Zhang. 2012. Rate control by R-lambda model for HEVC. ITU-T SG16 Contribution, JCTVC-K0103 (2012), 1–5.
    [17]
    Li Li, Bin Li, Houqiang Li, and Chang Wen Chen. 2016. \(\lambda\) -domain optimal bit allocation algorithm for high efficiency video coding. IEEE Transactions on Circuits and Systems for Video Technology 28, 1 (2016), 130–142.
    [18]
    Shengxi Li, Mai Xu, Zulin Wang, and Xiaoyan Sun. 2016. Optimal bit allocation for CTU level rate control in HEVC. IEEE Transactions on Circuits and Systems for Video Technology 27, 11 (2016), 2409–2424.
    [19]
    Woong Lim and Donggyu Sim. 2020. A perceptual rate control algorithm based on luminance adaptation for HEVC encoders. Signal, Image and Video Processing 14, 5 (2020), 887–895.
    [20]
    Jielian Lin, Aiping Huang, Keke Zhang, Xu Wang, and Tiesong Zhao. 2022. \(\lambda\) -domain VVC rate control based on game theory. arXiv preprint arXiv:2205.03595 (2022).
    [21]
    Feiyang Liu and Zhenzhong Chen. 2021. Multi-objective optimization of quality in VVC rate control for low-delay video coding. IEEE Transactions on Image Processing 30 (2021), 4706–4718.
    [22]
    Zhengyi Luo, Chen Zhu, Yan Huang, Rong Xie, Li Song, and C.-C. Jay Kuo. 2021. VMAF oriented perceptual coding based on piecewise metric coupling. IEEE Transactions on Image Processing 30 (2021), 5109–5121.
    [23]
    Yunhao Mao, Meng Wang, Shiqi Wang, and Sam Kwong. 2021. High efficiency rate control for versatile video coding based on composite cauchy distribution. IEEE Transactions on Circuits and Systems for Video Technology 32, 4 (2021), 2371–2384.
    [24]
    Zhaoqing Pan, Xiaokai Yi, Yun Zhang, Hui Yuan, Fu Lee Wang, and Sam Kwong. 2020. Frame-level bit allocation optimization based On<!–?Brk?–> video content characteristics for HEVC. ACM Trans. Multimedia Comput. Commun. Appl. 16, 1, Article 15 (Mar.2020), 20 pages. DOI:
    [25]
    Reza Rassool. 2017. VMAF reproducibility: Validating a perceptual practical video quality metric. In 2017 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB ’17). 1–2. DOI:
    [26]
    Abdul Rehman and Zhou Wang. 2012. SSIM-inspired perceptual video coding for HEVC. In 2012 IEEE International Conference on Multimedia and Expo. IEEE, 497–502.
    [27]
    B. T. Series. 2012. Methodology for the subjective assessment of the quality of television pictures. Recommendation ITU-R BT (2012), 500–13.
    [28]
    Junjun Si, Siwei Ma, and Wen Gao. 2013. Efficient bit allocation and CTU level rate control for high efficiency video coding. In 2013 Picture Coding Symposium (PCS ’13). IEEE, 89–92.
    [29]
    G. J. Sullivan, J. Ohm, W.-J. Han, and T. Wiegand. 2012. Overview of the high efficiency video coding (HEVC) standard. IEEE Transactions on Circuits and Systems for Video Technology 22, 12 (2012), 1649–1668.
    [30]
    Alexis Michael Tourapis, Oscar Chi Lim Au, and Ming Lei Liou. 2000. Predictive motion vector field adaptive search technique (PMVFAST): Enhancing block-based motion estimation. In Visual Communications and Image Processing 2001, Vol. 4310. SPIE, 883–892.
    [31]
    Sima Valizadeh, Panos Nasiopoulos, and Rabab Ward. 2021. Improving compression efficiency of HEVC using perceptual coding. Multimedia Tools and Applications 80, 7 (2021), 10235–10254.
    [32]
    Gang Wang, Yongfei Zhang, Bo Li, Rui Fan, and Mingliang Zhou. 2018. A fast and HEVC-compatible perceptual video coding scheme using a transform-domain Multi-Channel JND model. Multimedia Tools and Applications 77, 10 (2018), 12777–12803.
    [33]
    Hao Wang, Li Song, Rong Xie, Zhengyi Luo, and Xiangwen Wang. 2018. Masking effects based rate control scheme for high efficiency video coding. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS ’18). IEEE, 1–5.
    [34]
    Peng Wang, Cui Ni, Zhe Li, and Guangyuan Zhang. 2019. Optimal CTU-level bit allocation in HEVC for low bit-rate applications. Multimedia Tools and Applications 78, 16 (2019), 23733–23747.
    [35]
    Shiqi Wang, Abdul Rehman, Kai Zeng, and Zhou Wang. 2015. SSIM-inspired two-pass rate control for high efficiency video coding. In 2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP ’15). IEEE, 1–5.
    [36]
    Jiangtao Wen, Meiyuan Fang, Minhao Tang, and Kuang Wu. 2015. R-(lambda) model based improved rate control for HEVC with pre-encoding. In 2015 Data Compression Conference. IEEE, 53–62.
    [37]
    Jinjian Wu, Guangming Shi, Weisi Lin, and C. C. Jay Kuo. 2016. Enhanced just noticeable difference model with visual regularity consideration. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP ’16). IEEE, 1581–1585.
    [38]
    Guoqing Xiang, Huizhu Jia, Lin Ding, Fan Yang, Yuan Li, and Xiaodong Xie. 2020. Perceptual CTU level bit allocation for AVS2. In 2020 IEEE International Conference on Consumer Electronics (ICCE ’20). IEEE, 1–4.
    [39]
    Guoqing Xiang, Huizhu Jia, Mingyuan Yang, Xinfeng Zhang, Xiaofeng Huang, Jie Liu, and Xiaodong Xie. 2018. A perceptually temporal adaptive quantization algorithm for HEVC. Journal of Visual Communication and Image Representation 50 (2018), 280–289.
    [40]
    Guoqing Xiang, Xinfeng Zhang, Xiaofeng Huang, Fan Yang, Chuang Zhu, Huizhu Jia, and Xiaodong Xie. 2021. Perceptual quality consistency oriented CTU level rate control for HEVC intra coding. IEEE Transactions on Broadcasting 68, 1 (2021), 69–82.
    [41]
    Long Xu, Weisi Lin, Lin Ma, Yongbing Zhang, Yuming Fang, King Ngi Ngan, Songnan Li, and Yihua Yan. 2016. Free-energy principle inspired video quality metric and its use in video coding. IEEE Transactions on Multimedia 18, 4 (2016), 590–602.
    [42]
    Mai Xu, Lai Jiang, Xiaoyan Sun, Zhaoting Ye, and Zulin Wang. 2016. Learning to detect video saliency with HEVC features. IEEE Transactions on Image Processing 26, 1 (2016), 369–385.
    [43]
    Yunyao Yan, Guoqing Xiang, Yuan Li, Xiaodong Xie, and Huizhu Jia. 2020. An adaptive spatio-temporal perception aware quantization algorithm for AVS2. Journal of Visual Communication and Image Representation 73 (2020), 102917.
    [44]
    Chuohao Yeo, Hui Li Tan, and Yih Han Tan. 2013. SSIM-based adaptive quantization in HEVC. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 1690–1694.
    [45]
    Hui Yuan, Sam Kwong, Xu Wang, Wei Gao, and Yun Zhang. 2015. Rate distortion optimized inter-view frame level bit allocation method for MV-HEVC. IEEE Transactions on Multimedia 17, 12 (2015), 2134–2146.
    [46]
    Hui Yuan, Ju Liu, Jiangtao Ren, and Yujun Li. 2014. Coding modes-based frame skip avoidance scheme for low bit rate video coding. Journal of Real-time Image Processing 9 (2014), 609–619.
    [47]
    Hui Yuan, Qun Wang, Qi Liu, Junyan Huo, and Peng Li. 2021. Hybrid distortion-based rate-distortion optimization and rate control for H. 265/HEVC. IEEE Transactions on Consumer Electronics 67, 2 (2021), 97–106.
    [48]
    Zeming Zhao, Shuhua Xiong, Weiheng Sun, Xiaohai He, and Feiran Zhang. 2021. An improved R- \(\lambda\) rate control model based on joint spatial-temporal domain information and HVS characteristics. Multimedia Tools and Applications 80, 1 (2021), 345–366.
    [49]
    Mingliang Zhou, Xuekai Wei, Cheng Ji, Tao Xiang, and Bin Fang. 2022. Optimum quality control algorithm for versatile video coding. IEEE Transactions on Broadcasting (2022).
    [50]
    Mingliang Zhou, Xuekai Wei, Shiqi Wang, Sam Kwong, Chi-Keung Fong, Peter H. W. Wong, Wilson Y. F. Yuen, and Wei Gao. 2019. SSIM-based global optimization for CTU-level rate control in HEVC. IEEE Transactions on Multimedia 21, 8 (2019), 1921–1933.
    [51]
    Mingliang Zhou, Yongfei Zhang, Bo Li, and Xupeng Lin. 2017. Complexity correlation-based CTU-level rate control with direction selection for HEVC. ACM Trans. Multimedia Comput. Commun. Appl. 13, 4, Article 53 (Aug.2017), 23 pages. DOI:

    Cited By

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    • (2024)STSG: A Short Text Semantic Graph Model for Similarity Computing Based on Dependency Parsing and Pre-trained Language ModelsApplied Artificial Intelligence10.1080/08839514.2024.232155238:1Online publication date: 4-Mar-2024

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    Published In

    cover image ACM Transactions on Multimedia Computing, Communications, and Applications
    ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 20, Issue 5
    May 2024
    650 pages
    ISSN:1551-6857
    EISSN:1551-6865
    DOI:10.1145/3613634
    • Editor:
    • Abdulmotaleb El Saddik
    Issue’s Table of Contents

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 January 2024
    Online AM: 13 December 2023
    Accepted: 24 November 2023
    Revised: 04 November 2023
    Received: 03 March 2023
    Published in TOMM Volume 20, Issue 5

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    Author Tags

    1. Rate control
    2. HEVC
    3. perceptual distortion model
    4. Lagrange multiplier
    5. distortion dependency

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    • (2024)STSG: A Short Text Semantic Graph Model for Similarity Computing Based on Dependency Parsing and Pre-trained Language ModelsApplied Artificial Intelligence10.1080/08839514.2024.232155238:1Online publication date: 4-Mar-2024

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