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An alternating iterative algorithm for image deblurring and denoising problems

机译:图像去模糊和去噪问题的交替迭代算法

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摘要

In this paper, a modified l_1, minimization model for image delurring and denoising prob lems is considered. To solve the proposed /, minimization model, we present an efficient alternative iterative algorithm in which the fast iterative shrinkge-thresholding method (FISTA) and the well known dual approach for solving the denosing problems are alternately employed. Besides, we prove the convergence of the proposed algorithm. Numerical results demonstrate the efficiency and viability of the proposed algorithm to restore the degraded images.
机译:在本文中,考虑了用于图像去噪和去噪问题的改进的l_1最小化模型。为了解决所提出的最小化模型,我们提出了一种有效的替代迭代算法,其中快速迭代收缩阈值方法(FISTA)和众所周知的双重解决方法被交替采用。此外,我们证明了该算法的收敛性。数值结果证明了该算法对退化图像的复原效率和可行性。

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