You-Kaveh图像去噪模型扩散系数的改进
首发时间:2008-09-17
摘要:本文在You-Kaveh模型的基础上,提出了一个新的扩散系数,得到了一个去噪效果更好的方程,新方程不但能够去除高斯噪声,而且能够很好的去除椒盐噪声。同时,改进了模型中拉普拉斯算子的离散形式,使其包含更多的图像信息,能够更准确的判断图像的特征。 本文方法处理后的图像,避免了二阶偏微分方程处理图像常出现的“阶梯”效应,同时,和同类的四阶偏微分方程去噪模型相比,本文方法的处理结果不会出现“斑”点,因此视觉效果更加理想。最后,通过实验证明了该方法的有效性。
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An Improved Coefficient of You-Kaveh’s Image Denoising Model
Abstract:In this paper, a new diffusion coefficient is proposed. And a new partial differential equation is obtained. The new equation can not only remove the Gsussian noise, but also remove the salt-pepper noise. Meanwhile, the discretization scheme of Laplace operator is improved, and more image information can be contained. Thus, the image features can be judged more accurately. The image processed by the proposed model do not occur the blocky effects which are widely seen in images processed by second-order nonlinear diffusion. And compared to other fourth-order partial differential equations, the image processed by the proposed model do not generate the speckles, so the visual effects are superior to the image processed by You-Kaveh model. Finally, the validity of the proposed model is proved by experiments.
Keywords: image denoising fourth-order PDEs salt-pepper noise
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No.2411314953312216****
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