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Multiplicative noise removal through fractional order tv-based model and fast numerical schemes for its approximation

机译:通过基于电视的基于电视的模型和快速数字方案的乘法噪声去除,其近似值

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This paper introduces a fractional order total variation (FOTV) based model with three different weights in the fractional order derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is a highly non-linear partial differential equation (PDE) is obtained by the minimization of the energy functional for image restoration. Two numerical schemes namely an iterative scheme based on the dual theory and majorization--minimization algorithm (MMA) are used. To improve the restoration results, we opt for an adaptive parameter selection procedure for the proposed model by applying the trial and error method. We report numerical simulations which show the validity and state of the art performance of the fractional-order model in visual improvement as well as an increase in the peak signal to noise ratio comparing to corresponding methods. Numerical experiments also demonstrate that MMAbased methodology is slightly better than that of an iterative scheme.
机译:本文介绍了基于数分的总变化(FOTV)模型,具有三种不同权重的模型,用于乘法阶数定义,用于乘法噪声清除目的。作为高度非线性偏微分方程(PDE)的分数级欧拉拉格朗日等式是通过最小化图像恢复的能量功能而获得的。使用两个数值方案即,使用基于双理论和多种化最小化算法(MMA)的迭代方案。为了提高恢复结果,我们通过应用试验和错误方法选择所提出的模型的自适应参数选择过程。我们报告了数值模拟,其显示了视觉改进中的分数阶模型的现有性能的有效性和状态,以及与相应方法相比,峰值信号与噪声比的增加。数值实验还证明MMABASED方法略高于迭代方案。

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