浏览全部资源
扫码关注微信
Received：09 November 2019，
Revised：2020-5-13，
Accepted：20 May 2020，
Published：16 February 2021
移动端阅览
目的
2
随着云计算和移动互联网技术的飞速发展，屏幕图像编码已成为视频压缩领域新的研究热点。帧内块复制（intra block copy，IBC）算法是屏幕内容编码（screen content coding，SCC）中的核心算法，已经成为高效视频编码（high efficiency video coding，HEVC）等标准中屏幕内容编码的重要组成部分。为了进一步消除IBC算法中的位移矢量（displacement vector，DV）参数编码的冗余，根据DV参数具有的固有帧内块匹配特性和相关性，提出了一种DV参数编码算法。
方法
2
首先，对待编码DV采用邻近块与最近块相结合的DV预测编码方案，进一步提高DV的预测编码效率；然后，对预测编码效率不高的DV，提出了一种基于区域划分与调整的高效DV直接编码方案。对SCC标准测试数据集合中的17个测试数据集合的3种编码配置从编码效率和复杂度两方面进行了评测。
结果
2
实验结果表明，对于SCC标准测试数据集合中移动的文字和图形序列类别，在全帧内、随机接入和低延迟这3种有损编码配置下，提出的DV算法与HEVC SCC中的IBC算法相比，在编解码复杂度没有任何影响的前提下，
Y
分量的BD（Bjφntegaard Delta）-rate平均降低率分别为1.04%、0.87%和0.93%，全帧内配置下
Y
分量的BD-rate降低率可达2.99%。
结论
2
本文方法优于HEVC-SCC中的IBC算法中的DV编码算法，能有效提升编码效率。
Objective
2
With the recent rapid development of technologies in cloud computing and mobile internet
screen content coding (SCC) has become a key technology in many popular applications
such as videoconferencing with document or slide sharing
remote desktop
screen sharing
mobile or external display interfacing
and cloud gaming. Typical computer screen content contains a mixture of camera-captured and screen contents. Screen content exhibits highly different characteristics and varied levels of human's visual sensitivity to distortion compared with traditional camera-captured content. Screen content videos are typically not noisy
with sharp edges and multiple repeated patterns. New coding tools for better utilizing the correlation characteristics of screen content are necessary. Accordingly
SCC has become a popular topic in multimedia applications in recent years and has elicited increasing research attention from academia and industry. Several international video coding standards include efficient SCC capability
such as high efficiency video coding (HEVC)
versatile video coding (VVC)
and second-generation and third-generation audio video coding standard (AVS2 and AVS3
respectively). Repeated identical patterns (i.e.
matching patterns) are frequently observed on the same picture of screen content. Two major SCC tools in HEVC SCC were developed in recent years to utilize these repeated identical patterns with a variety of sizes and shapes. These tools are intra block copy (IBC) and palette coding. IBC
also called intra picture block compensation or current picture referencing
is a highly efficient technique for improving coding performance. It is effective for coding repeated identical patterns with a few fixed sizes and shapes. IBC is a direct extension of the traditional inter-prediction technique for the current picture
wherein a current prediction block is predicted from a reference block located in the already reconstrcted regions of the same picture. IBC has been adopted in the HEVC SCC extensions
VVC
and AVS3. In IBC
a displacement vector (DV) is used to signal the relative displacement from the position of the current block to that of the reference block. The coding efficiency of IBC primarily depends on the coding efficiency of DV. The existing DV coding algorithm used in HEVC SCC is the same as the motion vector coding algorithm used in the inter-prediction scheme. However
the existing DV coding algorithm only utilizes the correlations among the DVs of neighboring blocks. Moreover
intra block and inter block matching characteristics exhibit numerous differences. Thus
in accordance with the inherent intra block matching characteristics and different correlations of DV parameters in the IBC algorithm
we propose an improved DV algorithm for further increasing the coding efficiency of IBC.
Method
2
The DV to be coded has been proven to exhibit numerous correlations not only with neighboring blocks but also with recently coded blocks. To utilize the correlations of DVs with neighboring and recently coded blocks
we first apply an improved DV coding algorithm that adaptively uses DV predictions from either neighboring or recently coded blocks. Second
a direct DV coding scheme that uses a DV region division algorithm and a DV adjusting algorithm is proposed to eliminate redundancies further in the existing DV coding algorithm. Lastly
we evaluate coding performance and complexity on 17 test datasets from the SCC standard test dataset with three encoding configurations. In particular
13 sequences are selected to represent the most common screen content videos
referred to as the "text and graphics with motion" (TGM) category
and 4 sequences are selected to represent a mixture of natural video and text/graphics
referred to as the "mixed content" category.
Result
2
Experimental results show that the proposed algorithm achieves average
Y
BD-rate reductions of up to 1.04%
0.87%
and 0.93% for the TGM category of the SCC common test sequences with lossy all intra (AI)
random access
and low-delay B configurations
respectively
compared with the latest HEVC SCC at the same encoding and decoding runtimes. The maximum
Y
Bjφntegaard Delta(BD)-rate reduction reaches 2.99% in the AI configuration.
Conclusion
2
The experiment results demonstrate that our algorithm outperforms the DV coding algorithm for IBC in HEVC SCC.
AVS Group. 2016. AVS-N2282. Common test condition for screen and mixed content coding in AVS2-P2. Hangzhou: 1-4
AVS工作组. 2016. AVS-N2282, AVS2-P2屏幕与混合内容视频编码(SMCVC)通用测试条件.杭州: 1-4
Bjøntegaard G. 2001. ITU-T SG16 Q.6 Document VCEG-M33. Calculation of Average PSNR Differences Between RD-Curves. Austin: 1-3
Chen J, Ye Y and Kim S. 2020. JVET-Q2002. Algorithm description for versatile video coding and test model 8 (VTM 8). Brussels: 1-92
JCT-VC. 2019. HEVC SCC test software[EB/OL].[2019-03-22] . https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/tags/HM-16.20+SCM-8.8/ https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/tags/HM-16.20+SCM-8.8/
Li Y M, Xu X Z, Chen Z Z, Liu S, Zhou Q Y, Zhao L P, Lin T, Zhou K L, Ye Z G, Yang Y F and Jiao M C. 2019. AVS M4859. Block-matching based screen and mixed content coding technology combining M4766 (IBC) and M4815 (single-string mode in Universal String Prediction). Chengdu: 1-5
李一鸣, 许晓中, 陈震中, 刘杉, 周青阳, 赵利平, 林涛, 周开伦, 叶子高, 杨玉芬, 焦孟草. 2019. AVS M4859.融合M4766(IBC)、M4815(USP的单串模式)的基于块匹配的屏幕与混合内容编码技术.成都: 1-5
Lin T, Zhang P J, Wang S H, Zhou K L and Chen X Y. 2013. Mixed chroma sampling-rate high efficiency video coding for full-chroma screen content. IEEE Transactions on Circuits and Systems for Video Technology, 23(1): 173-185[DOI: 10.1109/TCSVT.2012.2223871]
Ma S W, Luo F L and Huang T J. 2017. Kernel technologies and applications of AVS2 video coding standard. Telecommunications Science, (8): 2017245
马思伟, 罗法蕾, 黄铁军. 2017. AVS2视频编码标准技术特色及应用.电信科学, (8): 2017245
Miyazawa K Y, Akira M Z and Sekiguchi S I. 2014. JCTVC-R0074. Non-SCCE1: adaptive switching between differential and direct coding for intra block copy vectors. Sapporo: 1-3
Pang C, Sole J, Chen Y, Karczewicz M, Xu X Z, Liu S, Chuang T D, Lei S M, Zhu L H, Xu J Z and Sullivan G J. 2014. JCTVC-R0309. Non-SCCE1: combination of JCTVC-R0185 and JCTVC-R0203//Proceedings of the 18th JCT-VCMeeting. Sapporo, Japan: [s.n.]: 1-7
Peng W H, Walls F G, Cohen R A, Xu J Z, Ostermann J, MacInnis A and Lin T. 2016. Overview of screen content video coding: technologies, standards, and beyond. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 6(4): 393-408[DOI: 10.1109/JETCAS.2016.2608971]
Tourapis A M, Su Y and Singer D. 2015. JCTVC-U0142. Inter/Intra block copy unification: comments and observations. Warsaw: 1-3
Xu X Z, Liu S, Chuang T D and Lei S M. 2015. Block vector prediction for intra block copying in HEVC screen content coding//Proceedings of 2015 Data Compression Conference. Snowbird: IEEE: 273-282[ DOI: 10.1109/DCC.2015.22 http://dx.doi.org/10.1109/DCC.2015.22 ]
Xu X Z, Liu S, Chuang T D, Huang Y W, Lei S M, Rapaka K, Pang C, Seregin V, Wang Y K and Karczewicz M. 2016. Intra block copy in HEVC screen content coding extensions. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 6(4): 409-419[DOI: 10.1109/JETCAS.2016.2597645]
Yu H P, Cohen R, Rapaka K and Xu J Z. 2017. JCTVC-Z1015. Common test conditions for screen content coding. Geneva: 1-8
Zhao L P, Lin T, Guo J and Zhou K L. 2019a. Universal string prediction-based inter coding algorithm optimization in AVS2 mixed content coding. Chinese Journal of Computers, 42(10): 2190-2202
赵利平, 林涛, 郭靖, 周开伦. 2019a.基于通用串预测算法的AVS2屏幕混合内容帧间编码优化.计算机学报, 42(10): 2190-2202)[DOI: 10.11897/SP.J.1016.2019.02190]
Zhao L P, Lin T and Zhou K L. 2017. An efficient ISC offset parameter coding algorithm in screen content coding. Chinese Journal of Computers, 40(5): 1218-1228
赵利平, 林涛, 周开伦. 2017.屏幕图像压缩中串复制位移参数的高效编码算法.计算机学报, 40(5): 1218-1228)[DOI: 10.11897/SP.J.1016.2017.01218]
Zhao L P, Lin T, Zhou K L, Wang S H and Chen X Y. 2016. Pseudo 2D string matching technique for high efficiency screen content coding. IEEE Transactions on Multimedia, 18(3): 339-350[DOI: 10.1109/TMM.2015.2512539]
Zhao L P, Zhou K L, Guo J, Cai W T, Lin T and Zhu R. 2018. Pixel string matching for full-chroma screen and mixed content coding in AVS2. Chinese Journal of Computers, 41(11): 2482-2495
赵利平, 周开伦, 郭靖, 蔡文婷, 林涛, 朱蓉. 2018.融合像素串匹配的AVS2全色度屏幕与混合内容视频编码算法.计算机学报, 41(11): 2482-2495)[DOI: 10.11897/SP.J.1016.2018.02482]
Zhao L P, Zhou K L, Guo J, Wang S H and Lin T. 2018. A universal string matching approach to screen content coding. IEEE Transactions on Multimedia, 20(4): 796-809[DOI: 10.1109/TMM.2017.2758519]
Zhao L P, Zhou K L, Lin T and Guo J. 2019b. A universal string prediction approach and its application in AVS2 mixed content coding. Chinese Journal of Computers, 42(9): 2100-2113
赵利平, 周开伦, 林涛, 郭靖. 2019b.通用串预测算法及在AVS2屏幕与混合内容视频编码中的应用.计算机学报, 42(9): 2100-2113)[DOI: 10.11897/SP.J.1016.2019.02100]
相关作者
相关机构
京公网安备11010802024621
