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一种基于信号局部时变特性的细节保护自适应滤波器

郭炳庆 卢强 黎雄

郭炳庆, 卢强, 黎雄. 一种基于信号局部时变特性的细节保护自适应滤波器[J]. 电子与信息学报, 2001, 23(11): 1050-1055.
引用本文: 郭炳庆, 卢强, 黎雄. 一种基于信号局部时变特性的细节保护自适应滤波器[J]. 电子与信息学报, 2001, 23(11): 1050-1055.
Guo Bingqing, Lu Qiang, Li Xiong . A KIND OF DETAIL-PRESERVING ADAPTIVE FILTER BASED ON LOCAL SIGNAL TIME-VARYING CHARACTERISTICS[J]. Journal of Electronics & Information Technology, 2001, 23(11): 1050-1055.
Citation: Guo Bingqing, Lu Qiang, Li Xiong . A KIND OF DETAIL-PRESERVING ADAPTIVE FILTER BASED ON LOCAL SIGNAL TIME-VARYING CHARACTERISTICS[J]. Journal of Electronics & Information Technology, 2001, 23(11): 1050-1055.

一种基于信号局部时变特性的细节保护自适应滤波器

A KIND OF DETAIL-PRESERVING ADAPTIVE FILTER BASED ON LOCAL SIGNAL TIME-VARYING CHARACTERISTICS

  • 摘要: 作者根据局部时序信号与顺序统计量的关系提出了一种新的自适应滤波器算法,并研究了该算法的几项主要性质。理论分析与仿真结果表明,依据时序信号与标准中值滤波器根信号之一的单调顺序统计量的相似性度量所确定的自适应滤波器具有有效抑制复杂分布噪声、保护信号边缘及细节的良好性能。
  • I. Pitas, A. N. Venetsanopoulos, Nonlinear Digital Filters, Norwell, MA: Kluwer, 1990, ch.3. [2]C.L. Nikas, A. P. Petropulu, Higher-Order Spectra Analysis, Englewood Cliffs, NJ, Prentice-Hall,1993, ch.4.[2]J. Mathews, Adaptive polynomial filters, IEEE Signal Processing Mag. , 1991, 8(4), 10-26.[3]T.H. Koh, E. J. Powers, Second-order Volterra filtering and its application to nonlinear systemidentification, IEEE Trans. on ASSP, 1985, 33(6), 1445-1455.[4]B.J. Justusson, Median Filtering: Statistic Properties in Two-Dimensional Digital Signal Pro-cessing, T. S. Huang Ed., New York, Springer-Verlag, 1981, vol.2, ch.4.[5]A.C. Bovik, T. S. Huang, D. C. Munson, A generalization of median filtering using linear combinations of order statistics, IEEE Trans. on ASSP, 1983, 31(6), 1342 1350.[6]G.R. Arce, N. C. Gallagher, T. Nodes, Median Filters: Theory and Applications, Advances in Computer Vision and Image Processing, T. S. Huang Ed. Greenwich, CT: JAI Press, 1986, ch.5. [8]G. R. Arce, R. E. Foster, Detail-preserving ranked-order based filters for inage processing, IEEE Trans. on ASSP, 1989, 37(1), 83-98.[7]R. Bernstein, Adaptive nonlinear filters for simultaneous removal of different kinds of noise inimages, IEEE Trans. on CAS, 1987, 34(11), 1275 1291.[8]X.Z. Sun, A. N. Venetsanopoulos, Adaptive schemes for noise filtering and edge detection by use of local statistics, IEEE Trans. on CAS, 1988, 35(1), 57 69.[9]P. Salembier, Adaptive rank order based filters, Signal Processing, 1992, 27(1), 1 25.[10]K.E. Barner, G. R. Arce, Permutation Filters: A class of nonlinear filters based on set permuta-tion, IEEE Trans. on SP, 1994, 42(4), 782 798.[11]Y.T. Kim , G. R. Arce, Permutation filter lattices: A general order-statistic filtering framework, IEEE Trans. on SP, 1994, 42(9), 2227-2241.[12]G.R. Arce, T. A. Hall, K. E. Barner, Permutation weighted order statistic filter lattices, IEEE Trans. on IP, 1995, 4(8), 1070-1083.[13]G.R. Arce, N. C. Gallagher, State description for root signal set of median filter, IEEE Trans.on ASSP, 1982, 30(4), 894-902.[14]J. P. Fitch , E. J. Coyle et al., Root properties and convergence rates of median filter, IEEETrans. on ASSP, 1985, 33(1), 230 240.
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出版历程
  • 收稿日期:  2000-04-06
  • 修回日期:  2000-10-16
  • 刊出日期:  2001-11-19

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