基于PDE的双曲-抛物型前向扩散图像去噪模型

IF 1.1 Q2 MATHEMATICS, APPLIED
Santosh Kumar, Khursheed Alam
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引用次数: 0

摘要

在本研究中,我们提出了一种有效的基于非线性各向异性扩散的双曲抛物面模型,用于图像去噪和边缘检测。双曲-抛物型模型采用二阶偏微分方程,并具有对时间t的二阶时间导数。这种方法对于保留噪声图像的更清晰的边缘和更好的去噪图像非常有效。我们的模型是适定的,并且在某些条件下具有唯一的弱解,这是通过使用迭代有限差分显式格式获得的。使用具有前向-后向扩散率的显式方案,以峰值信噪比(PSNR)作为度量来获得结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PDE-based hyperbolic-parabolic model for image denoising with forward-backward diffusivity
In the present study, we propose an effective nonlinear anisotropic diffusion-based hyperbolic parabolic model for image denoising and edge detection. The hyperbolic-parabolic model employs a second-order PDEs and have a second-time derivative to time t. This approach is very effective to preserve sharper edges and better-denoised images of noisy images. Our model is well-posed and it has a unique weak solution under certain conditions, which is obtained by using an iterative finite difference explicit scheme. The results are obtained in terms of peak signal to noise ratio (PSNR) as a metric, using an explicit scheme with forward-backward diffusivities.
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来源期刊
CiteScore
2.20
自引率
27.30%
发文量
0
审稿时长
4 weeks
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