A game theory approach for joint blind deconvolution and inpainting

N. Nasr, N. Moussaid, O. Gouasnouane
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引用次数: 0

Abstract

In this paper we propose a new mathematical model for joint Blind Deconvolution and Inpainting. The main objective is the treatment of blurred images with missing parts, through the game theory framework, in particular, a Nash game, we define two players: Player 1 handles the image intensity while Player 2, operates on the blur kernel. The two engage in a game until the equilibrium is reached. Finally, we provide some numerical examples: we compare the efficiency of our proposed approach to other existing methods in the literature that deals with Blind Deconvolution and Inpainting separately.
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一种联合盲反卷积和补图的博弈论方法
本文提出了一种新的联合盲反卷积和补图的数学模型。主要目标是处理缺失部分的模糊图像,通过博弈论框架,特别是纳什博弈,我们定义了两个参与者:参与者1处理图像强度,而参与者2操作模糊核。这两个人进行博弈,直到达到平衡。最后,我们提供了一些数值例子:我们将所提出的方法与文献中其他分别处理盲反卷积和图像修复的方法的效率进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Modeling and Computing
Mathematical Modeling and Computing Computer Science-Computational Theory and Mathematics
CiteScore
1.60
自引率
0.00%
发文量
54
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