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文章基本信息

  • 标题:Nonlinear Image Restoration Using a Radial Basis Function Network
  • 本地全文:下载
  • 作者:Keiji Icho ; Youji Iiguni ; Hajime Maeda
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2004
  • 卷号:2004
  • 期号:16
  • 页码:2441-2450
  • DOI:10.1155/S1110865704408166
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    We propose a nonlinear image restoration method that uses the generalized radial basis function network (GRBFN) and a regularization method. The GRBFN is used to estimate the nonlinear blurring function. The regularization method is used to recover the original image from the nonlinearly degraded image. We alternately use the two estimation methods to restore the original image from the degraded image. Since the GRBFN approximates the nonlinear blurring function itself, the existence of the inverse of the blurring process does not need to be assured. A method of adjusting the regularization parameter according to image characteristics is also presented for improving restoration performance.

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