高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于局部亮度直方图的自适应视频帧类型决策算法

刘鹏宇 张悦 贾克斌 段堃 刘畅 孙萱 崔腾鹤

刘鹏宇, 张悦, 贾克斌, 段堃, 刘畅, 孙萱, 崔腾鹤. 基于局部亮度直方图的自适应视频帧类型决策算法[J]. 电子与信息学报, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199
引用本文: 刘鹏宇, 张悦, 贾克斌, 段堃, 刘畅, 孙萱, 崔腾鹤. 基于局部亮度直方图的自适应视频帧类型决策算法[J]. 电子与信息学报, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199
LIU Pengyu, ZHANG Yue, JIA Kebin, DUAN Kun, LIU Chang, SUN Xuan, CUI Tenghe. Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram[J]. Journal of Electronics & Information Technology, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199
Citation: LIU Pengyu, ZHANG Yue, JIA Kebin, DUAN Kun, LIU Chang, SUN Xuan, CUI Tenghe. Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram[J]. Journal of Electronics & Information Technology, 2023, 45(1): 300-307. doi: 10.11999/JEIT211199

基于局部亮度直方图的自适应视频帧类型决策算法

doi: 10.11999/JEIT211199
基金项目: 国家重点研发计划(2018YFF01010100),北京自然科学基金(4212001),青海省重点研发与转化计划(2022-QY-205)
详细信息
    作者简介:

    刘鹏宇:女,副教授,博士生导师,研究方向为多媒体信息处理

    张悦:女,硕士生,研究方向为视频编码技术

    贾克斌:男,教授,博士生导师,研究方向为信息与通信系统

    段堃:男,硕士,研究方向为视频编码技术

    刘畅:女,博士生,研究方向为3D视频编码

    孙萱:男,硕士生,研究方向为视频编码技术

    崔腾鹤:男,硕士,研究方向为视频编码技术

    通讯作者:

    刘鹏宇 liupengyu@bjut.edu.cn

  • 中图分类号: TN919.81

Adaptive Video Frame Type Decision Algorithm Based on Local Luminance Histogram

Funds: The National Key Research and Development Program of China (2018YFF01010100), The Beijing Natural Science Foundation (4212001), The Key R&D and Transformation Program of Qinghai Province (2022-QY-205)
  • 摘要: 视频帧类型决策是影响视频编码效率的关键因素之一。为提升x265视频编码器的编码性能,该文提出基于局部亮度直方图的自适应视频帧类型决策算法。首先,在64×64大小的编码树单元(CTU)级别上统计各帧局部亮度直方图,用帧间局部亮度直方图差异表征帧间场景变换程度;其次,引入帧内编码帧(I帧)检测窗,在检测窗内通过比较帧间场景变换程度自适应确定I帧;最后,根据帧间场景变换程度与迷你图像组(MiniGOP)大小之间的相关性确定MiniGOP大小,从而自适应确定普通P和B帧(GPB帧)及双向预测编码帧(B帧)。实验结果表明,与x265标准中的相关算法相比,所提算法能够有效降低x265的编码复杂度,可在减少近5%编码时间的前提下,实现视频I帧、GPB帧和B帧的高效自适应决策。
  • 图  1  GOP示意图

    图  2  基于局部亮度直方图的自适应视频帧类型决策算法流程图

    图  3  某场景切换处前后两帧全局亮度直方图和CTU局部亮度直方图

    图  4  I帧检测过程

    图  5  MiniGOP示意图

    表  1  全局亮度直方图差异$ {D_{{\text{hist}}}} $与局部亮度直方图差异$ {D_{{\text{local\_hist}}}} $比较

    序列总帧数场景切换数$ {D_{{\text{hist}}}} > {D_{{\text{local\_hist}}}} $的场景切换数${D_{ {\text{hist} } } } < {D_{ {\text{local\_hist} } } }$的场景切换数
    Kimono240101
    送你一朵小红花408992092
    战狼244231850185
    F1赛车越野18804800
    下载: 导出CSV

    表  2  本场景切换检测算法与x265和参考文献[11]的检测准确度对比

    序列分辨率场景切换数x265参考文献[11]本文算法
    P(%)R(%)P(%)R(%)P(%)R(%)
    Traffic2560×16000100100100100100100
    Kimono1920×10801100100100100100100
    FourPeople1280×7200100100100100100100
    BQMall832×4800100100100100100100
    RaceHorses416×2400100100100100100100
    送你一朵小红花1920×10569289.3964.1376.1952.1710081.52
    战狼21280×72018596.2583.2471.8837.3097.6790.81
    红海行动1280×72013189.3632.0672.9741.2295.5481.68
    变形金刚51280×7205293.7557.6973.5348.0895.8388.46
    F1赛车越野960×5404886.8468.7574.1947.9293.3387.50
    下载: 导出CSV

    表  3  本场景切换检测与x265算法运行耗时对比(μs)

    序列分辨率x265本文算法
    Traffic2560×160046071.3634.13
    Kimono1920×108017382.7512.77
    FourPeople1280×7206774.904.93
    BQMall832×4802069.151.46
    RaceHorses416×240662.110.92
    下载: 导出CSV

    表  4  本文算法与x265中两种算法和参考文献[13]的算法性能比较

    Class序列x265快速x265 Viterbi参考文献[13]本文算法
    BDPSNR$ \Delta T $(%)BDPSNR$ \Delta T $(%)BDPSNR$ \Delta T $(%)BDPSNR$ \Delta T $(%)
    Class ATraffic2.6181.623–1.2362.5130.6051.590.524–1.170
    PeopleOnStreet0.1390.510–2.1953.2400.0201.07–1.056–0.532
    Class BCactus5.7422.681–0.6156.3680.3610.233.8920.216
    Kimono–1.2421.592–2.2622.4250.115–3.38–1.369–1.579
    Class CBasketballDirll4.1672.4120.1067.5920.6321.25–1.3150.822
    PartyScene8.1636.423–1.1934.7150.5530.842.1250.583
    Class DBasketballPass1.2034.741–2.0074.230.4875.271.773–0.836
    RaceHorses–0.2764.285–1.0539.5420.1961.75–1.741–1.474
    Class EFourPeople3.6582.1301.5072.7760.9512.89–3.773–0.256
    vidyo41.6463.3592.1192.0340.6222.45–1.410–0.572
    Class FSlideShow–0.8923.824–6.3645.1861.4941.59–9.727–0.119
    SlideEditing–0.6722.535–7.3828.5710.4172.15–10.631–1.658
    平均值2.0213.010–1.7154.9330.5371.475–1.892–0.548
    下载: 导出CSV
  • [1] JCT-VC. ITU-T Recommendation H. 265 High efficiency video coding[S]. Geneva: ITU–T, 2013.
    [2] CORREA G, ASSUNCAO P, AGOSTINI L, et al. Performance and computational complexity assessment of high-efficiency video encoders[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(12): 1899–1909. doi: 10.1109/TCSVT.2012.2223411
    [3] BOSSEN F, BROSS B, SUHRING K, et al. HEVC complexity and implementation analysis[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(12): 1685–1696. doi: 10.1109/TCSVT.2012.2221255
    [4] GAO Yuan, LIU Pengyu, WU Yueying, et al. Quadtree degeneration for HEVC[J]. IEEE Transactions on Multimedia, 2016, 18(12): 2321–2330. doi: 10.1109/TMM.2016.2598481
    [5] ESAKKI G, PANAYIDES A, TEEPARTHI, et al. A comparative performance evaluation of VP9, x265, SVT-AV1, VVC codecs leveraging the VMAF perceptual quality metric[J]. SPIE, 2020: 1151010.
    [6] x265 ORG. x265 HEVC encoder[EB/OL]. http://www.x265.org/, 2017.
    [7] 段堃. 基于H. 265/HEVC的高压缩率与低复杂度编码技术研究[D]. [硕士论文], 北京工业大学, 2020.

    DUAN Kun. Research on hight compression rate and low complexity coding based on H. 265/HEVC[D]. [Master dissertation], Beijing University of Technology, 2020.
    [8] FUAD M, ERNAWAN F, and HUI L J. Video scene change detection based on histogram analysis for hiding message[J]. Journal of Physics:Conference Series, 2021, 1918(4): 042141. doi: 10.1088/1742-6596/1918/4/042141
    [9] KANG S J. Positional analysis-based scene-change detection algorithm[C]. Proceedings of 2015 IEEE International Conference on Consumer Electronics, Las Vegas, USA, 2015: 11–12.
    [10] CHO S I and KANG S J. Histogram shape-based scene-change detection algorithm[J]. IEEE Access, 2019, 7: 27662–27667. doi: 10.1109/ACCESS.2019.2898889
    [11] 刘辉, 刘立程, 郝禄国, 等. 一种场景切换下的HEVC码率控制算法[J]. 电视技术, 2017, 41(6): 1–5. doi: 10.16280/j.videoe.2017.06.001

    LIU Hui, LIU Licheng, HAO Luguo, et al. A rate control algorithm for HEVC based on scene change[J]. Video Engineering, 2017, 41(6): 1–5. doi: 10.16280/j.videoe.2017.06.001
    [12] VideoLAN ORG. x264, the best H. 264/AVC encoder[EB/OL]. https://www.videolan.org/developers/x264.html, 2013.
    [13] LIU Zhenyu, WANG Libo, LI Xiaobo, et al. Optimize x265 rate control: An exploration of lookahead in frame bit allocation and slice type decision[J]. IEEE Transactions on Image Processing, 2019, 28(5): 2558–2573. doi: 10.1109/TIP.2018.2887200
    [14] FORNEY G D. The viterbi algorithm[J]. Proceedings of the IEEE, 1973, 61(3): 268–278. doi: 10.1109/PROC.1973.9030
    [15] 《送你一朵小红花》“珍惜版”预告 导演韩延开启“生命三部曲”[EB/OL]. https://www.mgtv.com/b/348435/10455525.html?fpa=se&#38;lastp=so_result, 2020.

    A Little Red Flower. Clip: “Trilogy of Life” directed by Han Yan[EB/OL]. https://www.mgtv.com/b/348435/10455525.html?fpa=se&lastp=so_result, 2020.
    [16] 《战狼2》片段: 冷锋Rachel飙车智斗“雇佣兵”[EB/OL]. https://www.mgtv.com/l/100009562/4052086.html?lastp=so_result, 2017.

    Wolf Warriors 2. Clip: Leng Feng and Rachel compete with mercenaries[EB/OL]. https://www.mgtv.com/l/100009562/4052086.html?lastp=so_result, 2017.
    [17] 见过F1赛车越野吗? 红牛是真敢作, 2亿的车就这么糟蹋?[EB/OL]. https://v.youku.com/v_show/id_XMzQzNjQ1MjU1Mg==.html?spm=a2h0c.8166622.PhoneSokuUgc_2.dtitle, 2018.

    Have you ever seen an F1 car off-road?[EB/OL]. https://v.youku.com/v_show/id_XMzQzNjQ1MjU1Mg==.html?spm=a2h0c.8166622.PhoneSokuUgc_2.dtitle, 2018.
    [18] 《红海行动》“蛟龙逆袭”版预告 蛟龙突击队展现超强作战力[EB/OL]. https://www.mgtv.com/b/315515/4293086.html?fpa=se&#38;lastp=so_result, 2018.

    "Operation Red Sea" clip: Preview version of "Jiaolong Attack"[EB/OL]. https://www.mgtv.com/b/315515/4293086.html?fpa=se&lastp=so_result, 2018.
    [19] 《变形金刚5》 并肩作战预告 人类联手变形金刚拯救地球[EB/OL]. https://www.mgtv.com/b/308889/3994088.html?fpa=se&#38;lastp=so_result, 2017.

    Transformers 5 clip: Side by side trailer[EB/OL]. https://www.mgtv.com/b/308889/3994088.html?fpa=se&lastp=so_result, 2017.
    [20] BJØNTEGAARD G. Calculation of average PSNR differences between RD-curves[C]. Proceedings of the 13th Video Coding Experts Group Meeting, Austin, USA, 2001: 290–291.
  • 加载中
图(5) / 表(4)
计量
  • 文章访问数:  105
  • HTML全文浏览量:  61
  • PDF下载量:  22
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-11-01
  • 修回日期:  2022-03-25
  • 网络出版日期:  2022-04-15
  • 刊出日期:  2023-01-17

目录

    /

    返回文章
    返回