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基于块分割和上下文模型的视频编码算法

Video Coding Algorithm Based on Block Segmentation and Context Model
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摘要 树结构的构造适合小波图像编码,但并不适合视频编码,利用熵编码原理,提出了视频图像编码算法,先将每帧的残差补偿到原始序列,并通过块分割编码和上下文模型进行视频编码.研究结果表明:该算法在视觉质量、算法性能和编码效率上要优于传统的视频编码算法. The tree structure quantification suits the wavelet image coding but doesn t suit the video coding.By using entropy coding principle,the authors put forward the video coding algorithm based on block segmentation and context model,which firstly compensates the initial sequence for the residua of each frame and then carries out the normal coding.Results show that the visual quality,performance,and coding efficiency of the new algorithm are superior to those of the traditional video coding algorithm.
作者 陈炳权 刘宏立
机构地区 湖南大学电气与信息工程学院 吉首大学物理科学与信息工程学院
出处 《吉首大学学报（自然科学版）》 CAS 2010年第2期-,共4页 Journal of Jishou University(Natural Sciences Edition)
基金 湖南省教育厅科学研究项目(08C714)
关键词 块分割 上下文模型 编码效率 编码算法 残差补偿 block segmentation context model coding efficiency coding algorithm residual compensation
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献10

  • 1赵安邦,余赟,孙国仓,李关防,惠俊英.基于残差补偿的多描述视频编码[J].中国科学（F辑:信息科学）,2009,39(7):751-756. 被引量：1
  • 2杨永明,许超.一个基于小波包分解的率失真最优化块分割图像编码算法[J].中国科学（E辑）,2008,38(8):1204-1219. 被引量：4
  • 3Coifman R R,Wickerhauser M V.Entropy-based algorithm for best basis selection. IEEE Transactions on Information Theory . 1992
  • 4Wu X.High-order context modeling and embedded conditional entropy coding of wavelet coefficients for image compres-sion. Thirty-First Asilomar Conf. on Signal and Computers . 1997
  • 5Said A,Pearlman W.A New Fast and Efficient Image Coding Based on Set Partitioning in Hierarchical Trees. IEEE Trans on Circuits & Systems for Video Technology . 1996
  • 6Shapiro J M.Embedding image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing . 1993
  • 7David Taubman.High performance scalable image compression with EBCOT. IEEE Transactions on Image Processing . 2000
  • 8Taubman D,Marcellin M.JPEG2000: Image Compression, Fundamentals, Standards, and Practice. . 2002
  • 9Meyer F G,Averbuch A,Stromberg J O.Fast adaptive wavelet packet image compression. IEEE Transactions on Image Processing . 2000
  • 10Xiong Z,Ramchandran K,Orchard M.T.Wavelet Packet Image Coding Using Space-frequency Quantization. IEEE Transactions on Image Processing . 1998

二级参考文献39

  • 1Yang Y M, Xu C. Fast and efficient basis selection methods for embedded wavelet packet image coding. In: Int Conf on Image Analysis and Recognition (ICIAR'06), 2006. 480--492.
  • 2Shapiro J M. Embedded image coding using zerotrees of wavelet coefficients. IEEE.Trans Signal Process, 1993, 41 (10): 3445--3462.
  • 3Said A, Pearlman W A. A new, fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans Circ Syst Video Technol, 1996, 6(6): 243-250.
  • 4Liu Z, Karam LJ. An efficient embedded zerotree wavelet image codec based on intraband partitioning. In: IEEE Int Conf Image Process, vol 3, 2000. 162--165.
  • 5Pearlman W A, Islam A, Nagaraj N, et al. Efficient, low-complexity image coding with a set-partitioning embedded block coder. IEEE Trans Circ Syst Video Technol, 2004, 14(11): 1219--1235.
  • 6Schelkens P, Munteanu A, Barbarien J, et al. Wavelet coding of volumetric medical datasets. IEEE Trans Med Imag, 2003, 22(3): 441--458.
  • 7Wu X. High-order context modeling and embedded conditional entropy coding of wavelet coefficients for image compression. In: Thirty-First Asilomar Conf On Signal, and Computers, vol 2, 1997. 1378--1382.
  • 8Taubman D. High performance scalable image compression with EBCOT. IEEE Trans Image Process, 2000, 9(7):1158--1170.
  • 9Taubman D, Marcellin M W. JPEG2000 Image Compression Fundamentals, Standards and Practice. Kluwer Academic Publishers, 2002.
  • 10Coifrnan R R, Wickerhauser M V. Entropy-based algorithms for best basis selection. IEEE Trans Inform Theory, Special Issue on Wavelet Transforms and Multires. Signal Anal, 1992, 38(3): 713--718.

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吉首大学学报（自然科学版）
2010年 第2期

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