基于对象的可分级视频编码
|
摘要
随着计算机和通信技术的不断发展,在网络中实时传输视频等媒体信息成为一种必然趋势。然而当前网络的带宽有限且带宽是实时变化的,不同用户的网络情况也存在很大差异,这些都为网络实时传输视频流制造了困难。
解决这个问题最合适的方法就是可伸缩性的编码视频序列,可伸缩性编码通常将视频序列编码为基本层和增强层两个层,基本层码流是必须传输的,包含最基本的视频信息,码率较低。增强层是作为可选传输的,可以任意截断,带宽不足时甚至可以不传输,传输的增强层越多,解码出的图像质量就越好。由于这种方法生成的视频流可以在一个很大的码率范围内自我调整,因而能够适应复杂的网络带宽波动。其次,由于增强层的数据包丢失不会影响到其它帧,对视频质量影响也不大,因而可伸缩性视频编码生成的视频流具有较好的鲁棒性。
但是这种方法的编码效率较低,和传统的非分级编码方法相比要低3db左右。为了提高它的编码效率,本文重点分析了分级编码和基于对象编码的研究现状,并在此基础上提出了一种基于对象的可分级视频编码方法。该方法在增强层运用了运动补偿技术,提高了编码效率;引入高空间分辨率增强层,获得较好的空间可分级性,可以应用在需要改变空间分辨率的视频传输中;在位平面编码时采用选择性增强技术,提高了感兴趣区域的视频质量。
通过NS-2网络模拟器进行了仿真试验,结果表明该方法提高了编码效率和图像质量,并且可以提供视频的空间可分级性。
With the development of computer and communications technology,real-time video and media transmission becomes an inevitable trend.However,the bandwidth of network is limited and real-time changed and the networks of different users are significantly different at the same time,which are the reasons for the difficulties of real-time video and media transmission.
The scalable video coding sequence is the most suitable method to solve above problem. The video sequence is usually separated into two layers by scalable video coding,in which the basic layer and enhancement layer are included.The basic layer is must be transmitted,in which basic information is contained and bitrate is lower.The enhancement Layer is an option transmission,which can be cut off even non-transmission when the bandwidth is insufficient. So the enhancement layer transmission is more,the image quality is better.The scalable video streams are able to adapt to complicated fluctuations of network bandwidth because the video streams can be self-regulated within the scope of a large bitrate.Secondly,for the loss of enhancement layer data packet will not affect the other frame and the quality of video sequence,the video sequence generated by the scalable video coding has better robustness.
Whereas,the encoding rate of the scalable video is less efficient,which is low 3 db compared with the traditional non-hierarchical coding method.In order to improve coding efficiency,a new fine granular scalable video coding method based on the image object is introduced based on the analysis of the fine-granularity-scalable and the coding based on the image object,in which motion compensation technology in enhancement layer is employed to improve the coding efficiency.The high spatial resolution enhancement layer is induced to obtain a better classification,which can be applied in the transmission of the spatial resolution video that needed to be changed.The selectively enhance is utilized in while plane coding to improve the video quality of the interested region.
The simulation is carried on the NS-2 network simulator,which shows that the coding efficiency and the image quality can be improved and the video sequence space scalability can be provided,either.
解决这个问题最合适的方法就是可伸缩性的编码视频序列,可伸缩性编码通常将视频序列编码为基本层和增强层两个层,基本层码流是必须传输的,包含最基本的视频信息,码率较低。增强层是作为可选传输的,可以任意截断,带宽不足时甚至可以不传输,传输的增强层越多,解码出的图像质量就越好。由于这种方法生成的视频流可以在一个很大的码率范围内自我调整,因而能够适应复杂的网络带宽波动。其次,由于增强层的数据包丢失不会影响到其它帧,对视频质量影响也不大,因而可伸缩性视频编码生成的视频流具有较好的鲁棒性。
但是这种方法的编码效率较低,和传统的非分级编码方法相比要低3db左右。为了提高它的编码效率,本文重点分析了分级编码和基于对象编码的研究现状,并在此基础上提出了一种基于对象的可分级视频编码方法。该方法在增强层运用了运动补偿技术,提高了编码效率;引入高空间分辨率增强层,获得较好的空间可分级性,可以应用在需要改变空间分辨率的视频传输中;在位平面编码时采用选择性增强技术,提高了感兴趣区域的视频质量。
通过NS-2网络模拟器进行了仿真试验,结果表明该方法提高了编码效率和图像质量,并且可以提供视频的空间可分级性。
With the development of computer and communications technology,real-time video and media transmission becomes an inevitable trend.However,the bandwidth of network is limited and real-time changed and the networks of different users are significantly different at the same time,which are the reasons for the difficulties of real-time video and media transmission.
The scalable video coding sequence is the most suitable method to solve above problem. The video sequence is usually separated into two layers by scalable video coding,in which the basic layer and enhancement layer are included.The basic layer is must be transmitted,in which basic information is contained and bitrate is lower.The enhancement Layer is an option transmission,which can be cut off even non-transmission when the bandwidth is insufficient. So the enhancement layer transmission is more,the image quality is better.The scalable video streams are able to adapt to complicated fluctuations of network bandwidth because the video streams can be self-regulated within the scope of a large bitrate.Secondly,for the loss of enhancement layer data packet will not affect the other frame and the quality of video sequence,the video sequence generated by the scalable video coding has better robustness.
Whereas,the encoding rate of the scalable video is less efficient,which is low 3 db compared with the traditional non-hierarchical coding method.In order to improve coding efficiency,a new fine granular scalable video coding method based on the image object is introduced based on the analysis of the fine-granularity-scalable and the coding based on the image object,in which motion compensation technology in enhancement layer is employed to improve the coding efficiency.The high spatial resolution enhancement layer is induced to obtain a better classification,which can be applied in the transmission of the spatial resolution video that needed to be changed.The selectively enhance is utilized in while plane coding to improve the video quality of the interested region.
The simulation is carried on the NS-2 network simulator,which shows that the coding efficiency and the image quality can be improved and the video sequence space scalability can be provided,either.
引文
[1]Weiping Li.Bit-Plane Coding of DCT Coefficients for Fine Granularity Scalability,ISO/IEC JYCI/SC29/WG11,MPEG98/M3989,Oct1998.
[2]吴枫,李世鹏,张亚勤.渐进精细的可伸缩性视频编码.计算机学报,2000,(12):235-238.
[3]刘元超,王悦,李永全.一种改进的渐进精细可扩展性视频编码方法.长江大学学报,2005,(10):324-326.
[4]王峰,张珍明,何业军,朱光喜.PFGS比特平面编码的新研究.黄冈师范学院学报,2005,(06):213-215.
[5]孙晓艳,高文,吴枫,李世鹏,张亚勤.基于宏块的渐进精细可伸缩的视频编码.软件学报,2002,(11):1222-1225.
[6]张方,吴成柯,程培星,肖嵩.一种改进的可分级视频编码方法及网络传输研究.电子与信息学报,2005,(01):96-99.
[7]方勇,吴成柯,朱红.一种新的渐进精细可分级编码算法.电子学报,2004,(08):221-224.
[8]王琪,赵黎,吴枫,李世鹏.可伸缩性视频编码的码率分配算法.电子学报,2002,(02):111-115.
[9]Qi Wang,Feng Wu,Shipeng Li,Yuzhuo Zhong,Ya-Qin Zhang.Fine-granularity spatially scalable video coding,Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing(ICASSP),2001,(3):1801-1804.
[10]Chang Yung-chi,Su Chi-wei,Chan Wei-min.Interactive Content Aware Video Streaming System with Fine Granularity Scalablity.2006 Springer Science+Business Media,LLC.Manufactured in the Netherlands,2006.
[11]William H.R.E quitz,Thomas M.Cover.Successes refinement of information.Inform.Theory,1991.
[12]M.Domanski,A.Luczak,S.Mackowiak.Spatial-temporal scalability for MPEG video coding,IEEE Trans.Circuits Syst.Video Technol.,2000,(10):1088-1093.
[13]H.Katata,N.Ito,H.Kusao.Temporal-scalable coding based on image content,IEEE Trans.CircuitsSyst.Video Technol,1997,(7):52-59.
[14]肖自美.图像信息理论与压缩编码技术.广州:中山大学出版社2000.
[15]陈志波,何芸.面向Internet的视频编码技术:精细可分级性(FGS)的实现.中国图象图形学报.2001.06.
[16]Wei ping-Li. Overview of Fine Granularity Scalability in MPEG-4 VideoStandard,IEEE Transactions on circuits and systems for video technology, 2001,11(3):3321-3326.
[17] F. Ling,W. Li, H. Sun. Bitplan ecoding of DCT coefficients for image and video compression, in Proc. SPIEV isual Communications and Image Processing(VCIP), San Jose, CA, 1999, 25-27.
[18]Part-2 Visual, Amendment 4: Streaming Video Profile, Coding of Audio-Visual Objects, ISO/IEC14496-2/FPDAM4, July2000.
[19] Shipeng Li, Feng Wu, Ya-Qin Zhang. Study on a new approach to improve FGS video coding efficiency. ISO/IEC JTC1/SC29/WG11, M5583, Dec, 1999.
[20]Xiaoyan Sun, Feng Wu, Shipeng L, Wen Gao, Ya-Qin Zhang, Macroblock-based progressive fine granularity scalable( PFGS)video coding with flexiblet emporal-SNR scalablilities. Image Processing of 2001 International Conference on, 2001, 7-10.
[21]Qi Wang,Feng Wu,Shipeng U,Yuzhuo Zhong,Ya-Qin Zhang, Fine-granularity spatially scalable video coding, Acoustics, Speech, and Signal Processing, 2001.
[22]M. vander Schaar, H. Radha. A novel MPEG-4 based hybrid temporal-SNR scalablity for internet video. ICIP2000, Vancouver, British Columbia, Canada, 2000,10-13.
[23]Yuwen He. H.26L- based fine granularity scalable video coding. IEEE, 2000.
[24]Yuwen He, Improved Fine Granulars calable coding with Inter-Layer Prediction.The data compression conference, 2002.
[25]Marpe D,Blaterman G, Heising G. Technical of aquality-scalable coder for H.26L,ITU/SG16 Q15-K-12, Aug2000.
[26] Shapiro J M. Embedded image coding using zerotree of wavelet coefficients.IEEE Trans. Signal Processing, 1993, 41(12):34453462.
[27]A. Sald, W.A. Pearlman. A new fast and efficient image codec based on set partitioning inhierarchical trees, IEEE Trans. ClrcuitsSyst. VideoTechnol, 1996,(6):243-250.
[28]A. Zandi, J. Allen, E. Schwartz, M. Boliek. CREW: Compression with reversible embedded wavelets, IEEE Data Compression Conference, Snowbird, UT, 1995,212-221.
[29]C .Le Buhan,F.Bossen,S.Bhattachadee,F Jordan,T. Ebrahimi, Shape representation and coding of visual objects in multimedia applications-An Overview, (invited paper), in Annales des Telecommunications, 1998,(5-6): 164-178.
[30]MPEG-4 Video G roup, Generic Coding of Audio Visual Objects: Part2-Visual,ISO/IEC/JTC1/SC29/WG11 N1902,ISO/IEC FDIS 14496-2,Atlantic City,Nov.l998.
[31] F.Bossen,T.Ebrahimi, A simple and efficient binary shape coding technique based on bitmap representation, in Proc. of the International Conference on Acoustics,Speech, and Signal Processing(ICASSP'97), 1997, (4):3129-3132.
[32]J. Rissanen, G G Langdon. Arithmetic coding of IBM, 1979, (2):149-162.
[33]G G Langdon and J.Rissanen, Compression of black-white images with arithmetic coding, IEEE Trans. 1981, 29(6):858-867.
[34]C. Home. Unsupervised image segmentation, Ph.D.thesis, EPF-Lausanne,Lausanne, Switzerland, 1990.
[35]C. Go. Multivalued morphology and segmentation based on coding, Ph.D.thesis,EPF-Lausanne, Lausanne, Switzerland, 1995.
[36]E. Moscheni. Spatio-temporal segmentation and object tracking: An application tosecond generation video coding, Ph.D. thesis (1618), EPFL, Lausanne, Switzerland,1997.
[37]R.Castagno, Video segmentation based on multiple features for interactive and automatic multimedia applications, Ph.D.thesis (1894), EPFL, Lausanne, Switzerland,1998.
[38] The MPEG-4 Video Verification Model 18.0, ISO/IEC JTC1/SC29/WG11 N3908,Pisa, Jan.2001.
[39]Andre Kaup, Adaptive Low-Pass Extrapolation for Object-Based Texture Coding of Arbitrary Shaped Image Segments, in Proc. Visual Common. Image Processing'97,SPIE, 1997, (3024):731-741.
[40]Andre Kaup. Object Based Texture Coding of Moving Video in MPEG-4. IEEE Trans. On Circuits and Systems for Video Technology, 1999, (9):543-547.
[41]ITU-T: Video coding for low bitrate communication. International Telecommunications Union, Geneva, Switzerland, ITU-TR ecommendationH .263,1998.
[42]Cote Guy, et al. H.263+: Video coding at low bitrates. IEEE CSVT, 1998,849-866.
[43] Draft Text of Recommendation H.263 Version2 ("H.263+") for Decision, 1997.
[44]M. Ohta, S. Nogaki. Hybrid picture coding with wavelet transform and overlapped motion-compensated interframe prediction coding,IEEE Transactions on Signal Processing,1993,41(12):3416-3424.
[45]Radha H,M van der Schaar,Chen YW.The MPEG-4 fine Grained Scalable Video Coding Method for Multimedia Streaming over IP.IEEE Transactions on Multimedia,2001,53-68.
[46]Jiang Tao,Zhang Yaoyang,Ma Ran.Improved spatio-SNR FGS video coding scheme using motion compensation on enhancement-layer,Journal of Systems Engineering and Electronics,2006,17(1):37-42.
[47]NS Web Page:http://www.isi.edu/nsnam
[48]徐雷鸣,庞博,赵耀.NS与网络模拟.北京:人民邮电出版社,2003,12.
[2]吴枫,李世鹏,张亚勤.渐进精细的可伸缩性视频编码.计算机学报,2000,(12):235-238.
[3]刘元超,王悦,李永全.一种改进的渐进精细可扩展性视频编码方法.长江大学学报,2005,(10):324-326.
[4]王峰,张珍明,何业军,朱光喜.PFGS比特平面编码的新研究.黄冈师范学院学报,2005,(06):213-215.
[5]孙晓艳,高文,吴枫,李世鹏,张亚勤.基于宏块的渐进精细可伸缩的视频编码.软件学报,2002,(11):1222-1225.
[6]张方,吴成柯,程培星,肖嵩.一种改进的可分级视频编码方法及网络传输研究.电子与信息学报,2005,(01):96-99.
[7]方勇,吴成柯,朱红.一种新的渐进精细可分级编码算法.电子学报,2004,(08):221-224.
[8]王琪,赵黎,吴枫,李世鹏.可伸缩性视频编码的码率分配算法.电子学报,2002,(02):111-115.
[9]Qi Wang,Feng Wu,Shipeng Li,Yuzhuo Zhong,Ya-Qin Zhang.Fine-granularity spatially scalable video coding,Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing(ICASSP),2001,(3):1801-1804.
[10]Chang Yung-chi,Su Chi-wei,Chan Wei-min.Interactive Content Aware Video Streaming System with Fine Granularity Scalablity.2006 Springer Science+Business Media,LLC.Manufactured in the Netherlands,2006.
[11]William H.R.E quitz,Thomas M.Cover.Successes refinement of information.Inform.Theory,1991.
[12]M.Domanski,A.Luczak,S.Mackowiak.Spatial-temporal scalability for MPEG video coding,IEEE Trans.Circuits Syst.Video Technol.,2000,(10):1088-1093.
[13]H.Katata,N.Ito,H.Kusao.Temporal-scalable coding based on image content,IEEE Trans.CircuitsSyst.Video Technol,1997,(7):52-59.
[14]肖自美.图像信息理论与压缩编码技术.广州:中山大学出版社2000.
[15]陈志波,何芸.面向Internet的视频编码技术:精细可分级性(FGS)的实现.中国图象图形学报.2001.06.
[16]Wei ping-Li. Overview of Fine Granularity Scalability in MPEG-4 VideoStandard,IEEE Transactions on circuits and systems for video technology, 2001,11(3):3321-3326.
[17] F. Ling,W. Li, H. Sun. Bitplan ecoding of DCT coefficients for image and video compression, in Proc. SPIEV isual Communications and Image Processing(VCIP), San Jose, CA, 1999, 25-27.
[18]Part-2 Visual, Amendment 4: Streaming Video Profile, Coding of Audio-Visual Objects, ISO/IEC14496-2/FPDAM4, July2000.
[19] Shipeng Li, Feng Wu, Ya-Qin Zhang. Study on a new approach to improve FGS video coding efficiency. ISO/IEC JTC1/SC29/WG11, M5583, Dec, 1999.
[20]Xiaoyan Sun, Feng Wu, Shipeng L, Wen Gao, Ya-Qin Zhang, Macroblock-based progressive fine granularity scalable( PFGS)video coding with flexiblet emporal-SNR scalablilities. Image Processing of 2001 International Conference on, 2001, 7-10.
[21]Qi Wang,Feng Wu,Shipeng U,Yuzhuo Zhong,Ya-Qin Zhang, Fine-granularity spatially scalable video coding, Acoustics, Speech, and Signal Processing, 2001.
[22]M. vander Schaar, H. Radha. A novel MPEG-4 based hybrid temporal-SNR scalablity for internet video. ICIP2000, Vancouver, British Columbia, Canada, 2000,10-13.
[23]Yuwen He. H.26L- based fine granularity scalable video coding. IEEE, 2000.
[24]Yuwen He, Improved Fine Granulars calable coding with Inter-Layer Prediction.The data compression conference, 2002.
[25]Marpe D,Blaterman G, Heising G. Technical of aquality-scalable coder for H.26L,ITU/SG16 Q15-K-12, Aug2000.
[26] Shapiro J M. Embedded image coding using zerotree of wavelet coefficients.IEEE Trans. Signal Processing, 1993, 41(12):34453462.
[27]A. Sald, W.A. Pearlman. A new fast and efficient image codec based on set partitioning inhierarchical trees, IEEE Trans. ClrcuitsSyst. VideoTechnol, 1996,(6):243-250.
[28]A. Zandi, J. Allen, E. Schwartz, M. Boliek. CREW: Compression with reversible embedded wavelets, IEEE Data Compression Conference, Snowbird, UT, 1995,212-221.
[29]C .Le Buhan,F.Bossen,S.Bhattachadee,F Jordan,T. Ebrahimi, Shape representation and coding of visual objects in multimedia applications-An Overview, (invited paper), in Annales des Telecommunications, 1998,(5-6): 164-178.
[30]MPEG-4 Video G roup, Generic Coding of Audio Visual Objects: Part2-Visual,ISO/IEC/JTC1/SC29/WG11 N1902,ISO/IEC FDIS 14496-2,Atlantic City,Nov.l998.
[31] F.Bossen,T.Ebrahimi, A simple and efficient binary shape coding technique based on bitmap representation, in Proc. of the International Conference on Acoustics,Speech, and Signal Processing(ICASSP'97), 1997, (4):3129-3132.
[32]J. Rissanen, G G Langdon. Arithmetic coding of IBM, 1979, (2):149-162.
[33]G G Langdon and J.Rissanen, Compression of black-white images with arithmetic coding, IEEE Trans. 1981, 29(6):858-867.
[34]C. Home. Unsupervised image segmentation, Ph.D.thesis, EPF-Lausanne,Lausanne, Switzerland, 1990.
[35]C. Go. Multivalued morphology and segmentation based on coding, Ph.D.thesis,EPF-Lausanne, Lausanne, Switzerland, 1995.
[36]E. Moscheni. Spatio-temporal segmentation and object tracking: An application tosecond generation video coding, Ph.D. thesis (1618), EPFL, Lausanne, Switzerland,1997.
[37]R.Castagno, Video segmentation based on multiple features for interactive and automatic multimedia applications, Ph.D.thesis (1894), EPFL, Lausanne, Switzerland,1998.
[38] The MPEG-4 Video Verification Model 18.0, ISO/IEC JTC1/SC29/WG11 N3908,Pisa, Jan.2001.
[39]Andre Kaup, Adaptive Low-Pass Extrapolation for Object-Based Texture Coding of Arbitrary Shaped Image Segments, in Proc. Visual Common. Image Processing'97,SPIE, 1997, (3024):731-741.
[40]Andre Kaup. Object Based Texture Coding of Moving Video in MPEG-4. IEEE Trans. On Circuits and Systems for Video Technology, 1999, (9):543-547.
[41]ITU-T: Video coding for low bitrate communication. International Telecommunications Union, Geneva, Switzerland, ITU-TR ecommendationH .263,1998.
[42]Cote Guy, et al. H.263+: Video coding at low bitrates. IEEE CSVT, 1998,849-866.
[43] Draft Text of Recommendation H.263 Version2 ("H.263+") for Decision, 1997.
[44]M. Ohta, S. Nogaki. Hybrid picture coding with wavelet transform and overlapped motion-compensated interframe prediction coding,IEEE Transactions on Signal Processing,1993,41(12):3416-3424.
[45]Radha H,M van der Schaar,Chen YW.The MPEG-4 fine Grained Scalable Video Coding Method for Multimedia Streaming over IP.IEEE Transactions on Multimedia,2001,53-68.
[46]Jiang Tao,Zhang Yaoyang,Ma Ran.Improved spatio-SNR FGS video coding scheme using motion compensation on enhancement-layer,Journal of Systems Engineering and Electronics,2006,17(1):37-42.
[47]NS Web Page:http://www.isi.edu/nsnam
[48]徐雷鸣,庞博,赵耀.NS与网络模拟.北京:人民邮电出版社,2003,12.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |