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首页> 外文期刊>Frontiers in Applied Mathematics and Statistics >Minimizing Compositions of Functions Using Proximity Algorithms with Application in Image Deblurring
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Minimizing Compositions of Functions Using Proximity Algorithms with Application in Image Deblurring

机译：使用邻近算法最小化函数组成及其在图像去模糊中的应用

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摘要

We consider minimization of functions that are compositions of functions having closed-form proximity operators with linear transforms. A wide range of image processing problems including image deblurring can be formulated in this way. We develop proximity algorithms based on the fixed point characterization of the solution to the minimization problems . We further refine the proposed algorithms when the outer functions of the composed objective functions are separable. The convergence analysis of the developed algorithms is established. Numerical experiments in comparison with the well-known Chambolle-Pock algorithm and Zhang-Burger-Osher scheme for image deblurring are given to demonstrate that the proposed algorithms are efficient and robust.
机译：我们考虑函数的最小化，函数是具有线性变换的闭式接近算子的函数的组合。以此方式可以解决包括图像去模糊在内的各种图像处理问题。我们基于最小化问题的解的不动点特征开发邻近算法。当组成的目标函数的外部函数是可分离的时，我们进一步完善了提出的算法。建立了所开发算法的收敛性分析。通过与著名的Chambolle-Pock算法和Zhang-Burger-Osher方案进行图像去模糊的数值实验相比较，证明了所提算法的有效性和鲁棒性。

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