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首页> 外文期刊>SIAM Journal on Numerical Analysis >Piecewise linear approximation of the continuous Rudin-Osher-Fatemi model for image denoising
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Piecewise linear approximation of the continuous Rudin-Osher-Fatemi model for image denoising

机译:用于图像去噪的连续Rudin-Osher-Fatemi模型的分段线性逼近

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This paper is concerned with the numerical approximation of the minimizer of the continuous Rudin-Osher-Fatemi (ROF) model for image denoising. A new discrete total variation is proposed and the associated Hilbertian total variation denoising model is used to construct continuous piecewise linear functions that approximate the minimizer of the ROF model in the strong topology of L~ 2 (Ω), provided that the data function is bounded and weakly regular in the sense of Lip(α, L (Ω)).
机译:本文关注用于图像去噪的连续Rudin-Osher-Fatemi(ROF)模型的极小值的数值逼近。提出了一个新的离散总变化量,并使用关联的希尔伯特总变化去噪模型构造了连续的分段线性函数,该函数近似逼近L〜2(Ω)的强拓扑中ROF模型的最小值。在Lip(α,L(Ω))的意义上是弱规则的。

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