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基于多原子快速匹配追踪的图像编码算法

邓承志 汪胜前 曹汉强

邓承志, 汪胜前, 曹汉强. 基于多原子快速匹配追踪的图像编码算法[J]. 电子与信息学报, 2009, 31(8): 1807-1811. doi: 10.3724/SP.J.1146.2008.01150
引用本文: 邓承志, 汪胜前, 曹汉强. 基于多原子快速匹配追踪的图像编码算法[J]. 电子与信息学报, 2009, 31(8): 1807-1811. doi: 10.3724/SP.J.1146.2008.01150
Deng Cheng-zhi, Wang Sheng-qian, Cao Han-qiang. Multi-atoms Rapid Matching Pursuit-Based Image Coding Algorithm[J]. Journal of Electronics & Information Technology, 2009, 31(8): 1807-1811. doi: 10.3724/SP.J.1146.2008.01150
Citation: Deng Cheng-zhi, Wang Sheng-qian, Cao Han-qiang. Multi-atoms Rapid Matching Pursuit-Based Image Coding Algorithm[J]. Journal of Electronics & Information Technology, 2009, 31(8): 1807-1811. doi: 10.3724/SP.J.1146.2008.01150

基于多原子快速匹配追踪的图像编码算法

doi: 10.3724/SP.J.1146.2008.01150
基金项目: 

国家自然科学基金(60462003,60772091)资助课题

Multi-atoms Rapid Matching Pursuit-Based Image Coding Algorithm

  • 摘要: 该文提出一种多原子快速匹配追踪信号稀疏分解算法,并将其应用于静态图像编码。多原子匹配追踪通过每次迭代选取多个原子的形式,实现信号的快速稀疏分解。在此基础上,通过构造多尺度脊波字典实现图像的稀疏分解,并对稀疏分解的数据进行自适应量化和编码。实验结果表明,多原子匹配追踪获得了与匹配追踪相当的逼近性能,同时极大地提高了稀疏分解的速度。新的编码算法在低比特率情况下,获得了比JPEG2000更理想的编码性能。
  • Taubman D and Marcellin M. JPEG-2000: ImageCompression Fundantmentals, Standards and Practice [M].Massachusetts: Kluwer Academic Publishers, 2001: 212-379.[2]Mallat S and Zhang Z. Matching pursuit with time-frequencydictionaries [J].IEEE Transactions on Signal Processing.1993, 41(12):3397-3415[3]Gribonval R and Vandergheynst P. On the exponentialconvergence of matching pursuits in quasi-incoherentdictionaries [J].IEEE Transactions on Information Theory.2006, 52(1):255-261[4]Peotta L and Vandergheynst P. Matching pursuit with blockincoherent dictionaries [J].IEEE Transactions on SignalProcessing.2007, 55(9):4549-4557[5]Aharon M and Elad M. Sparse and redundant modeling ofimage content using an image-signature-dictionary [J].SIAMJournal on Imaging Sciences.2008, 1(3):228-247[6]Mairal J, Sapiro G, and Elad M. Learning multiscale sparserepresentations for image and video restoration [J].SIAMMultiscale Modeling and Simulation.2008, 7(1):214-241[7]Mairal J, Elad M, and Sapiro G. Sparse representation forcolor image restoration [J]. IEEE Transactions on ImageProcessing, 2008, 17(1): 53-69.[8]Ventura R M Figueras I, Vandergheynst P, and Frossard P.Low-rate and flexible image coding with redundantrepresentation [J].IEEE Transactions on Image Precessing.2006, 15(3):726-739[9]Gribonval R. Fast matching pursuit with a multiscaledictionary of gaussian chirps [J].IEEE Transactions onSignal Processing.2001, 49(5):994-1001[10]De Vleeschwouwer C and Macq B. Subband dictionaries forlow-cost matching pursuit of video residues [J].IEEETransactions on Circuits and Systems for Video Technology.1999, 9(7):984-993[11]Schmid-Saugeon P and Zakhor A. Dictionary design formatching pursuit and application to motion-compensatedvideo coding [J].IEEE Transactions on Circuits and Systemsfor Video Technology.2004, 14(6):880-886[12]Chou Y T, Hwang W L, and Huang C L. Gain-shapeoptimized dictionary for matching pursuit video coding [J].Signal Processing.2003, 83(9):1937-1943[13]Jost P, Vandergheynst P, and Frossard P. Tree-based pursuit:algorithm and properties [J].IEEE Transactions on SignalProcessing.2006, 54(12):4685-4697[14]Candes E J. Harmonic analysis of neural networks [J].Applied and Computational Harmonic Analysis.1999, 6(2):197-218[15]Shoa A and Shirani S. Adaptive quantization for matchingpursuit [C]. IEEE International Workshop on MultimediaSignal Processing, Victoria, Canada, Oct. 3-6, 2006: 71-74.
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出版历程
  • 收稿日期:  2008-09-16
  • 修回日期:  2009-01-05
  • 刊出日期:  2009-08-19

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