利用交替参数共轭梯度降低图像脉冲噪声

IF 1 Q1 MATHEMATICS

European Journal of Pure and Applied Mathematics Pub Date : 2023-07-30 DOI:10.29020/nybg.ejpam.v16i3.4849

Hawraz N. Jabbar, Yeldez J. Subhi, Basim A. Hassan

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引用次数: 0

摘要

共轭梯度法强调共轭公式。本研究使用Perry共轭条件和二次模型为共轭梯度方法恢复图像创建了一个新的共轭系数。算法具有全局收敛性和下降性。这项新技术在数值试验中表现更好。新的共轭梯度技术优于FR方法。这项新技术在数值试验中表现更好。新的共轭梯度技术优于FR方法。

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Image Impulse Noise Reduction Using a Conjugate Gradient of Alternative Parameter

Conjugate gradient approaches emphasise the conjugate formula. This study creates a new conjugate coefficient for the conjugate gradient approach to restore pictures using Perry’s conjugacy condition and a quadratic model. Algorithms have global convergence and descent. The new technique performed better in numerical testing. The new conjugate gradient technique outperforms the FR method. The new technique performed better in numerical testing. The new conjugate gradient technique outperforms the FR method.

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来源期刊

European Journal of Pure and Applied Mathematics MATHEMATICS-

CiteScore

1.30

自引率

28.60%

发文量

156