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Identification and Removal of Impulsive Noise from Corrupted Images Using Hypergraph Model

机译:使用超图模型识别和去除损坏图像中的脉冲噪声

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Image noise is unwanted information of an image. Noise can occur during image capture, transmission, or processing and it may depend or may not depend on image content. In order to remove the noise from the noisy image, prior knowledge about the nature of noise must be known otherwise noise removal causes the image blurring. Identifying nature of noise is a challenging problem. Many researchers have proposed their ideas on image denoising and each of them has its assumptions, advantages and limitations. In this paper, we are proposing a new algorithm for identifying and removing the impulsive noise using hypergraph concept.
机译:图像噪声是图像的有害信息。噪声可能会在图像捕获,传输或处理期间发生,并且可能取决于或可能不取决于图像内容。为了从噪声图像中去除噪声,必须知道关于噪声性质的先验知识,否则噪声去除会导致图像模糊。识别噪声的性质是一个具有挑战性的问题。许多研究人员提出了他们关于图像去噪的想法,每个人都有其假设,优点和局限性。在本文中,我们提出了一种使用超图概念识别和消除脉冲噪声的新算法。

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