Low-cost denoising and deblurring using a novel nonlinear diffusion technique

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED Journal of Computational and Applied Mathematics Pub Date : 2025-06-01 Epub Date: 2024-12-07 DOI:10.1016/j.cam.2024.116423
Lorella Fatone , Daniele Funaro
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引用次数: 0

Abstract

An algorithm for the treatment of images affected by both blurring and salt&pepper noise is proposed with a cost only proportional to the number of pixels. The methodology uses an ad-hoc discretization scheme for the Laplace operator, multiplied by a suitable nonlinear term depending on the gradient. Even if this approach resembles a diffusion type algorithm, only one step of the procedure is in general needed, leading to significant time savings. The procedure is successfully tested on some standard black&white images.
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采用新颖的非线性扩散技术进行低成本去噪和去模糊
提出了一种处理同时受模糊和椒盐噪声影响的图像的算法,其代价仅与像素数成正比。该方法使用拉普拉斯算子的特别离散化方案,根据梯度乘以合适的非线性项。即使这种方法类似于扩散类型算法,通常也只需要一个步骤,从而节省大量时间。该程序在一些标准的黑白图像上成功地进行了测试。
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来源期刊
CiteScore
5.40
自引率
4.20%
发文量
437
审稿时长
3.0 months
期刊介绍: The Journal of Computational and Applied Mathematics publishes original papers of high scientific value in all areas of computational and applied mathematics. The main interest of the Journal is in papers that describe and analyze new computational techniques for solving scientific or engineering problems. Also the improved analysis, including the effectiveness and applicability, of existing methods and algorithms is of importance. The computational efficiency (e.g. the convergence, stability, accuracy, ...) should be proved and illustrated by nontrivial numerical examples. Papers describing only variants of existing methods, without adding significant new computational properties are not of interest. The audience consists of: applied mathematicians, numerical analysts, computational scientists and engineers.
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