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浙江大学学报(工学版)
计算机技术﹑电信技术     
HEVC编码单元尺寸快速选择算法
周承涛1,2, 田翔1,2, 陈耀武1,2
1. 浙江大学 数字技术及仪器研究所,浙江 杭州 310027; 2. 浙江省网络多媒体技术研究重点实验室,浙江 杭州 310027
Fast coding unit size decision for HEVC
ZHOU Cheng-tao1,2, TIAN Xiang1,2, CHEN Yao-wu1,2
1. Institute of Advanced Digital Technology and Instrumentation, Zhejiang University, Hangzhou 310027, China; 2. Zhejiang Provincial Key Laboratory for Network Multimedia Technologies, Hangzhou 310027, China
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摘要:

针对高性能视频编码标准(HEVC)采用递归式的四叉树编码单元划分而引起的高计算复杂度问题,提出一种编码单元尺寸快速选择算法.该算法充分利用时空相邻编码单元深度的相关性.根据当前编码单元与左侧编码单元深度信息的相关性,提出深度单一性,利用这种特性,预测当前编码单元的深度搜索范围;根据前一帧中编码单元的深度信息判断编码单元所覆盖图像区域的复杂度,并根据该区域的复杂度进一步缩减可能的深度搜索,从而提高编码单元划分速度.结果表明,该算法与HEVC参考代码中的标准算法相比,在保证编码效率的前提下,编码时间可以平均节省约25%.该算法可以与HEVC编码器中的快速算法结合使用,进一步提高编码速度.

Abstract:

To reduce the coding computational complexity of the quadtree block partition process in high efficiency video coding (HEVC), a fast coding unit (CU) size decision based on the spatio-temporal correlation of CU depth was proposed. First, characteristic called depth monotonicity using the depth information of left CU was introduced to predict the depth of the current CU. Second, the spilt structure of the current CU was predicted using the similar structure of temporal neighboring CUs, as the spilt structure of the CU was highly related to the complexity of the region covered by CU. As compared to the original HEVC encoder, experimental results show that the proposed algorithm can save 25% encoding time on average with almost the same Rate-Distortion performance. The proposed algorithm can be incorporated with the fast algorithms adopted by HEVC reference software to maximize the encoder complexity reduction for HEVC.

出版日期: 2014-08-01
:  TP 391  
基金资助:

国家自然科学基金资助项目(40927001);中央高校基本科研业务费专项资金资助项目;浙江省重点科技创新团队资助项目(2011R09021-06).

通讯作者: 田翔,男,副教授     E-mail: tianx@mail.bme.zju.edu.cn
作者简介: 周承涛(1987—),男,博士,从事视频编解码算法以及嵌入式多媒体研究. E-mail: two@zju.edu.cn
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引用本文:

周承涛, 田翔, 陈耀武. HEVC编码单元尺寸快速选择算法[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2014.08.015.

ZHOU Cheng-tao, TIAN Xiang, CHEN Yao-wu. Fast coding unit size decision for HEVC. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2014.08.015.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2014.08.015        http://www.zjujournals.com/eng/CN/Y2014/V48/I8/1451

[1] SULLIVAN G J, OHM J R, HAN W J, et al. Overview of the high efficiency video coding (HEVC) standard [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(12): 1649-1668.
[2] VANNE J, VIITANEN M, HAMALAINEN T D, et al. Comparative rate-distrotion-complexity analysis of HEVC and AVC video codecs [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(12): 1885-1898.
[3] KIM J, CHOE Y, KIM Y-G. Fast coding unit size decision algorithm for intra coding in HEVC [C]∥ Proceedings of 2013 IEEE International Conference on Consumer Electronics. Las Vegas: IEEE, 2013: 637-638.
[4] WANG H, WEE Y, KIM Y, et al. An early termination method using the residual in high efficiency video coding [C]∥ Proceedings of IEEE International Symposium on Broadband Multimedia Systems and Broadcasting. Seoul: IEEE, 2012.
[5] SHEN X, YU L, CHEN J. Fast coding unit size decision selection for HEVC based on Bayesian decision rule [C]∥ Proceedings of 2012 Picture Coding Symposium. Krakow: IEEE, 2012: 453-456.
[6] KIM J, JEONG S, CHO S, et al. Adaptive coding unit early termination algorithm for HEVC [C]∥ Proceedings of 2012 IEEE International Conference on Consumer Electronics. Las Vegas: IEEE, 2012: 261-262.
[7] SHEN L, LIU Z, ZHANG X, et al. An effective CU size decision method for HEVC encoders [J]. IEEE Transactions on Multimedia, 2013, 15(2): 465-470.
[8] LEE H, KIM K, KIM T, et al. Fast encoding algorithm based on depth of coding-unit for high efficiency video coding [J]. Optical Engineering, 2012, 51(6).
[9] GWEON R H, LEE Y L, LIM J. Early termination of CU encoding to reduce HEVC complexity \[EB/OL\] (2011-07)\[2013-09-25\]. http:∥phenix.int-evry.fr/jct/JCTVC-F045.doc
[10] CHOI K, PARK S H, JANG E S. Coding tree pruning based CU early termination \[EB/OL\](2011-07) \[2013-09-25\].http:∥phenix.int-evry.fr/jct/JCTVC-F092.doc
[11] YANG J, KIM J, WON K, et al. Early SKIP detection for HEVC \[EB/OL\] (2011-11) \[2013-09-25\]. http:∥phenix.int-evry.fr/jct/JCTVC-G543.doc
[12] BOSSEN F. Common test conditions and software reference configurations \[EB/OL\] (2012-10) \[2013-09-25\].http:∥phenix.int-evry.fr/jct/JCTVC-J1100.doc
[13] KIM I K, MCCANN K, SUGIMOTO K, et al. HM8: High efficiency video coding (HEVC) test model 8 encoder description \[EB/OL\] (2012-10) [2013-09-25].. http:∥phenix.int-evry.fr/jct/JCTVC-J1002.doc
[14] BJONTEGAARD G. Calculation of average PSNR differences between RD-curves \[EB/OL\] (2001-04) \[2013-09-25\]. wftp3.itu.int/av-arch/video-site/0104_Aus/VCEG-M33.doc

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