基于SOR迭代的图像模糊各向异性扩散方程数值评估

N A Basran, J. Eng, A. Saudi, J. Sulaiman
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引用次数: 0

摘要

在保留图像边缘等重要特征的同时模糊图像是计算机视觉中的一个重要研究课题。本文给出了用Jacobi、Gauss Seidel和连续过松弛(SOR)三种迭代方法求解图像模糊各向异性扩散方程的结果,其中Jacobi的输出图像作为控制图像。用求解各向异性扩散方程的迭代次数和计算时间来衡量所考虑的迭代方法的性能。研究结果表明,与Jacobi和Gauss-Seidel方法相比,SOR方法对图像内部区域的平滑效率更高,而Jacobi和Gauss-Seidel方法所需的迭代次数和计算时间最少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical Assessment of Anisotropic Diffusion Equation for Image Blurring Using SOR Iteration
Blurring the image while preserving the important features such as edges is a crucial study in computer vision. This paper presents the results of applying three iterative methods which are Jacobi, Gauss Seidel and Successive Overrelaxation (SOR) to solve anisotropic diffusion equation for image blurring, where the output image of Jacobi is used as a control image. The number of iterations and computational time required to solve the anisotropic diffusion equation are used to measure the performance of the considered iterative methods. The findings show that SOR method is more efficient to smooth the inner region of an image compared to Jacobi and Gauss-Seidel methods in which the SOR required the least number of iterations and computational time.
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