单向分布式视频编码中迭代相关性噪声细化方法
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摘要
针对单向分布式视频编码(UDVC),文中提出了迭代相关性噪声细化方法.在迭代解码过程中,利用上次解码的重构系数对相关性噪声进行细化,提高相关性噪声的估计精度,并且在细化过程中根据系数的解码可靠性对残差进行分类加权细化来避免错误解码系数对细化的误导.实验结果表明,经过相关性噪声细化后,重构帧中由于码率欠估计导致的质量退化问题得到了明显的改善,不同视频序列重构WZ帧的平均峰值信噪比(PSNR)可以提高0.32～0.13 dB;和未细化的单向DVC相比,文中基于相关性噪声细化的单向DVC系统的整体平均PSNR也提高了约0.21 dB.
An iterative correlation noise refinement(CNR) method was proposed for unidirectional distributed video coding(UDVC). In the iterative decoding process, the correlation noise was refined by using the previously reconstructed coefficients to improve the accuracy of correlation noise modeling. During the refinement, the correlation noise residuals were classified according to the decoding reliability and weighted refined respectively in order to avoid misleading refinement caused by wrongly decoded coefficients. Experimental results show that the reconstruction quality is greatly improved after CNR. The average peak signal-to-noise ratio(PSNR) of reconstructed WZ frames from different video sequences is improved by 0.32～0.13 dB. Compared with UDVC without CNR, the average PSNR of the proposed UDVC with CNR is improved by 0.21 dB.
An iterative correlation noise refinement(CNR) method was proposed for unidirectional distributed video coding(UDVC). In the iterative decoding process, the correlation noise was refined by using the previously reconstructed coefficients to improve the accuracy of correlation noise modeling. During the refinement, the correlation noise residuals were classified according to the decoding reliability and weighted refined respectively in order to avoid misleading refinement caused by wrongly decoded coefficients. Experimental results show that the reconstruction quality is greatly improved after CNR. The average peak signal-to-noise ratio(PSNR) of reconstructed WZ frames from different video sequences is improved by 0.32～0.13 dB. Compared with UDVC without CNR, the average PSNR of the proposed UDVC with CNR is improved by 0.21 dB.
引文
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[14] 唐振华,梁祥严,覃团发,等.分布式视频编码中基于多概率混合分布的相关噪声建模方法 [J].电子学报,2015,43(2):365- 370.TANG Zhen-hua,LIANG Xiang-yan,QIN Tuan-fa,et al.Correlation noise modeling algorithm based on multiple probability distributions for distributed video coding [J].Acta Electronica Sinica,2015,43(2):365- 370.
[15] 刘杰平,何越盛.DVC中基于广义高斯分布的WZ帧重构算法 [J].华南理工大学学报(自然科学版),2014,42(8):77- 83.LIU Jie-ping,HE Yue-sheng.Generalized Gaussian distribution based WZ frame reconstruction algorithm for distributed video coding [J].Journal of South China University of Technology(Natural Science Edition),2014,42(8):77- 83.
[16] 刘欢.单向分布式视频编码中迭代解码技术研究 [D].西安:西安电子科技大学,2018.
[2] PEREIRA F,TORRES L,GUILLEMOT C,et al.Distributed video coding:selecting the most promising application scenarios [J].Image Communication,2008,23(5):339- 352.
[3] SLEPIAN D,WOLF J.Noiseless coding of correlated information sources [J].IEEE Transactions on Information Theory,1973,19(4):471- 480.
[4] WYNER A,ZIV J.The rate-distortion function for source coding with side information at the decoder [J].IEEE Transactions on Information Theory,1976,22(1):1- 10.
[5] AARON A,SETTON E.Transform-domain Wyner-Ziv codec for video [C]//Proceedings of Visual Communications and Image Processing.San Jose,CA:SPIE,2004:520- 528.
[6] ARTIGAS X,ASCENSO J,DALAI M,et al,The DISCOVER codec:architecture,techniques and evaluation [C]//Proceedings of Picture Coding Symposium.Lisbon,Portugal:IEEE,2007:1- 4.
[7] SONG J,SHEN P,ZHANG L,et al.An encoder rate control method for unidirectional distributed video coding [C]//Proceedings of SPIE,Satellite Data Compression,Communication and Processing.San Diego,California:SPIE,2013:21- 25.
[8] HU C,HU B,TU W,et al.A low-complexity and efficient encoder rate control solution for distributed residual video coding [J].Multimedia Tools & Applications,2017,77(9):1- 23.
[9] 胡春筠,胡斌杰.基于伪随机码置乱的分布式视频残差编码端码率控制算法 [J].电子学报,2016,44(6):1490- 1495.HU Chun-yun,HU Bin-jie.Encoder rate control algorithm based on scrambling with pseudo-random code for distri-buted residual coding of video [J].Acta Electronica Sinica,2016,44(6):1490- 1495.
[10] BRITES C,PEREIRA F.An efficient encoder rate control solution for transform domain Wyner-Ziv video co-ding [J].IEEE Transactions on Circuits Systems and Video Technology,2011,21(9):1278- 1292.
[11] BRITES C,PEREIRA F.Correlation noise modeling for efficient pixel and transform domain Wyner-Ziv video coding [J].IEEE Transactions on Circuits Systems and Video Technology,2008,18(9):1177- 1190.
[12] MOHAMMAD Y,AHMADM O,Swamy M N.A joint co-rrelation noise estimation and decoding algorithm for distributed video coding [J].Multimedia Tools & Applications,2018,77(9):1- 29.
[13] SONG J,LI Y,WANG K,et al.Distributed video coding with progressive correlation noise refinement and maximum likelihood pre-decoding [J].Optical Engineering,2012,51(7):7401- 7412.
[14] 唐振华,梁祥严,覃团发,等.分布式视频编码中基于多概率混合分布的相关噪声建模方法 [J].电子学报,2015,43(2):365- 370.TANG Zhen-hua,LIANG Xiang-yan,QIN Tuan-fa,et al.Correlation noise modeling algorithm based on multiple probability distributions for distributed video coding [J].Acta Electronica Sinica,2015,43(2):365- 370.
[15] 刘杰平,何越盛.DVC中基于广义高斯分布的WZ帧重构算法 [J].华南理工大学学报(自然科学版),2014,42(8):77- 83.LIU Jie-ping,HE Yue-sheng.Generalized Gaussian distribution based WZ frame reconstruction algorithm for distributed video coding [J].Journal of South China University of Technology(Natural Science Edition),2014,42(8):77- 83.
[16] 刘欢.单向分布式视频编码中迭代解码技术研究 [D].西安:西安电子科技大学,2018.