A noise cancellation algorithm based on hypergraph modeling

A. Bretto, H. Cherifi
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引用次数: 9

Abstract

Although the binary relations used in proximity graphs are relevant for many basic situations, they cannot represent the structuration process of digital images. In this paper we show that hypergraph theory is a more appropriate frame to describe the neighborhood relations that can be formalized between pixels. We illustrate the effectiveness of such a model by deriving a noise cancellation algorithm based on a basic combinatoric property of hypergraphs.
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一种基于超图建模的噪声消除算法
虽然接近图中使用的二值关系与许多基本情况相关,但它们不能代表数字图像的结构过程。在本文中,我们证明了超图理论是一个更合适的框架来描述可以形式化的像素之间的邻域关系。我们通过推导基于超图的基本组合性质的噪声消除算法来说明这种模型的有效性。
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