Ieee Transactions on Image Processing Fast, Robust Total Variation{based Reconstruction of Noisy, Blurred Images
Ieee Transactions on Image Processing Fast, Robust Total Variation{based Reconstruction of Noisy, Blurred Images
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通讯作者：
C. Vogel;M. Oman
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作者：
C. Vogel;M. Oman
| 利用改进的全变分正则化泛函进行Tikhonov正则化，从噪声、模糊数据中恢复图像。这种方法适用于图像处理，因为它不对解图像设置先验平滑条件。本文提出了一种有效的离散化算法，它将处理非线性的定点迭代与处理大型线性方程组的一种新的、有效的预条件共轭梯度迭代相结合。重建，收敛结果，并与快速线性求解器的直接比较，卫星图像重建应用。
| Tikhonov regularization with a modiied total variation regularization functional is used to recover an image from noisy, blurred data. This approach is appropriate for image processing in that it does not place a priori smoothness conditions on the solution image. An eecient algorithm is presented for the discretized problem which combines a xed point iteration to handle nonlinearity with a new, eeective preconditioned conjugate gradient iteration for large linear systems. Reconstructions, convergence results, and a direct comparison with a fast linear solver are presented for a satellite image reconstruction application .