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Adaptive Box-Constrained Total Variation Image Restoration Using Iterative Regularization Parameter Adjustment Method

机译:迭代正则化参数调整方法的自适应盒约束全变分图像复原

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摘要

In this paper, we consider the problem of image restoration with box-constraints. Image restoration problem is ill-conditioned and the regularization approach has widely been used to stabilize the solution. The restored image highly depends on the choice of the regularization parameter. The regularization parameter is generally determined by trial-and-error method when no true original image is available. Obviously, it is time consuming. The main aim in this paper is to develop an algorithm to choose the regularization parameter automatically when the box-constraints are imposed. In the proposed algorithm, the regularization parameter is adaptively determined by the previous iterative solution. Numerical simulations are used to demonstrate the performance of the proposed method.
机译:在本文中,我们考虑了具有框约束的图像恢复问题。图像恢复问题病态严重,正则化方法已广泛用于稳定解决方案。恢复的图像高度取决于正则化参数的选择。当没有真实的原始图像可用时,通常通过试错法确定正则化参数。显然,这很耗时。本文的主要目的是开发一种在施加框约束时自动选择正则化参数的算法。在提出的算法中,正则化参数由先前的迭代解决方案自适应地确定。数值模拟用来证明该方法的性能。

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