基于扩散过程的文档图像盲增强

Mohamed Riad Yagoubi, A. Serir, Azeddine Beghdadi
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引用次数: 3

摘要

文档图像增强是一个深入研究的领域。许多基于非线性各向异性扩散的方法已被证明可以有效地去除一些常见的伪影,如渗光。然而,所提出的方法在去除渗血伪影同时加强原始侧划方面有些无效。本文的目的是提出一种新的非线性各向异性扩散方法,该方法可以增强前景边缘的相干性,同时平滑地去除背景伪影。该方法基于结构张量,使用一个新的参数,可以更好地区分前景和伪影特征。利用张量特征值,用一组新的方程来表示扩散格式。该系统允许在前景/背景笔画之间执行第二次区分。通过对实际图像的客观测量和感知判断,对所提增强方案的性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind document image enhancement based on diffusion process
Document image enhancement is a well investigated field of research. Many approaches based on nonlinear anisotropic diffusion have been proved efficient for removing some common artifacts such as bleed-through. However, the proposed methods are somewhat ineffective in removing bleed-through artifacts while strengthening original side strokes. The purpose of this work is to propose a novel nonlinear anisotropic diffusion approach which enhances foreground edges coherence while smoothly removes background artifacts. The proposed method is based on a structure tensor using a new parameter which permits to better distinguish between foreground and artifacts characters. The diffusion scheme is expressed through a new set of equations using the tensor eigenvalues. This system allows to perform a second discrimination between foreground/background strokes. The performance of the proposed enhancement scheme is evaluated by means of objective measures and perceptual judgment of the obtained results on real images.
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