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ITERATIVE ALGORITHMS BASED ON DECOUPLING OF DEBLURRING AND DENOISING FOR IMAGE RESTORATION

机译:基于去噪和去噪去耦的图像恢复迭代算法

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摘要

In this paper, we propose iterative algorithms for solving image restoration problems. The iterative algorithms are based on decoupling of deblurring and denoising steps in the restoration process. In the deblurring step, an efficient deblurring method using fast transforms can be employed. In the denoising step, effective methods such as the wavelet shrinkage denoising method or the total variation denoising method can be used. The main advantage of this proposal is that the resulting algorithms can be very efficient and can produce better restored images in visual quality and signal-to-noise ratio than those by the restoration methods using the combination of a data-fitting term and a regularization term. The convergence of the proposed algorithms is shown in the paper. Numerical examples are also given to demonstrate the effectiveness of these algorithms.
机译:在本文中,我们提出了解决图像恢复问题的迭代算法。迭代算法基于恢复过程中去模糊和去噪步骤的解耦。在去模糊步骤中,可以采用使用快速变换的有效去模糊方法。在去噪步骤中,可以使用诸如小波收缩去噪方法或总变化去噪方法的有效方法。该提议的主要优点是,与使用数据拟合项和正则项的组合的恢复方法相比,所产生的算法可以非常高效,并且在视觉质量和信噪比方面可以产生更好的恢复图像。 。文中给出了所提算法的收敛性。数值例子也证明了这些算法的有效性。

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