Large region inpainting by re-weighted regularized methods

IF 1.2 4区 数学 Q2 MATHEMATICS, APPLIED
Yiting Chen, Jia Li, Qingyun Yu
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引用次数: 2

Abstract

In the development of imaging science and image processing request in our daily life, inpainting large regions always plays an important role. However, the existing local regularized models and some patch manifold based non-local models are often not effective in restoring the features and patterns in the large missing regions. In this paper, we will apply a strategy of inpainting from outside to inside and propose a re-weighted matching algorithm by closest patch (RWCP), contributing to further enhancing the features in the missing large regions. Additionally, we propose another re-weighted matching algorithm by distance-based weighted average (RWWA), leading to a result with higher PSNR value in some cases. Numerical simulations will demonstrate that for large region inpainting, the proposed method is more applicable than most canonical methods. Moreover, combined with image denoising methods, the proposed model is also applicable for noisy image restoration with large missing regions.
采用重加权正则化方法绘制大面积区域
在成像科学的发展和我们日常生活中对图像处理的要求中,大面积的图像绘制一直扮演着重要的角色。然而,现有的局部正则化模型和一些基于补丁流形的非局部模型往往不能有效地恢复大面积缺失区域的特征和模式。在本文中,我们将采用从外到内的补图策略,并提出一种基于最接近补丁的重加权匹配算法(RWCP),有助于进一步增强缺失大区域的特征。此外,我们提出了另一种基于距离加权平均(RWWA)的重新加权匹配算法,在某些情况下得到了更高的PSNR值。数值模拟结果表明,对于大面积的喷漆,本文提出的方法比大多数标准方法更适用。此外,结合图像去噪方法,该模型也适用于缺失区域较大的噪声图像恢复。
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来源期刊
Inverse Problems and Imaging
Inverse Problems and Imaging 数学-物理:数学物理
CiteScore
2.50
自引率
0.00%
发文量
55
审稿时长
>12 weeks
期刊介绍: Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.
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