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A multigrid for image deblurring with Tikhonov regularization

机译:用Tikhonov正则化进行图像去模糊的多重网格

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摘要

In the resolution of certain image deblurring problems with given boundary conditions we obtain two-level structured linear systems. In the case of shift-invariant point spread function with Dirichlet (zero) boundary conditions, the blurring matrices are block Toeplitz matrices with Toeplitz blocks. If the periodic boundary conditions are used, then the involved structures become block circulant with circulant blocks. Furthermore, Gaussian-like point spread functions usually lead to numerically banded matrices which are ill-conditioned since they are associated to generating functions that vanish in a neighbourhood of (π,π). We solve such systems by applying a multigrid method. The proposed technique shows an optimality property, i.e. its cost is of O(N) arithmetic operations (like matrix–vector product), where N is the size of the linear system. In the case of images affected by noise we use two Tikhonov regularization techniques to reduce the noise effects.
机译:在给定边界条件下解决某些图像去模糊问题的过程中,我们获得了两级结构化线性系统。在具有Dirichlet(零)边界条件的不变位移点扩展函数的情况下,模糊矩阵是具有Toeplitz块的块Toeplitz矩阵。如果使用周期性边界条件,则所涉及的结构将成为带有循环块的循环块。此外,类高斯点扩展函数通常会导致数值带状矩阵处于不良状态,因为它们与生成在(π,π)附近消失的函数相关。我们通过应用多网格方法来解决此类系统。所提出的技术具有最优性,即其成本为O(N)个算术运算(如矩阵-矢量积),其中N为线性系统的大小。对于受噪声影响的图像,我们使用两种Tikhonov正则化技术来减少噪声影响。

著录项

  • 作者

    DONATELLI M.;

  • 作者单位
  • 年度 2005
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  • 原文格式 PDF
  • 正文语种 eng
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