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Correction to: Solution methods for linear discrete ill-posed problems for color image restoration

机译:更正为:用于彩色图像恢复的线性离散不适定问题的解决方法

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This work discusses four algorithms for the solution of linear discrete ill-posed problems with several right-hand side vectors. These algorithms can be applied, for instance, to multi-channel image restoration when the image degradation model is described by a linear system of equations with multiple right-hand sides that are contaminated by errors. Two of the algorithms are block generalizations of the standard Golub-Kahan bidiagonalization method with the block size equal to the number of channels. One algorithm uses standard Golub-Kahan bidiagonalization without restarts for all right-hand sides. These schemes are compared to standard Golub-Kahan bidiagonalization applied to each right-hand side independently. Tikhonov regularization is used to avoid severe error propagation. Numerical examples illustrate the performance of these algorithms. Applications include the restoration of color images.
机译:这项工作讨论了用几种右侧向量解决线性离散不适定问题的四种算法。当通过线性方程组描述图像退化模型时,这些算法可以应用于多通道图像恢复,其中线性方程组的多个右侧受到错误的污染。其中两种算法是标准Golub-Kahan双向对角化方法的块推广,其块大小等于通道数。一种算法使用标准的Golub-Kahan双角化,而无需为所有右侧重新启动。将这些方案与分别应用于每个右侧的标准Golub-Kahan双角化进行了比较。 Tikhonov正则化可避免严重的错误传播。数值示例说明了这些算法的性能。应用包括恢复彩色图像。

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