基于加权超图和IOWA算子的图像椒盐噪声滤除算法
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作者单位:

(1. 安徽大学计算机科学与技术学院,合肥230601;2. 安徽大学商学院,合肥230601)

作者简介:

徐沁(1983-), 女, 讲师, 从事图像处理与模式识别的研究;罗斌(1963-), 男, 教授, 博士生导师, 从事图像处理与模式识别等研究.

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E-mail: xuqin2013@aliyun.com

中图分类号:

TP391.41

基金项目:

国家自然科学基金项目(61502003, 71501002, 61472002, 61671018);安徽省自然科学基金项目(1608085 QF133, 1508085QG149).


Salt and pepper noise removing algorithm based on weighted hypergraph and IOWA operator
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(1. School of Computer Science and Technology,Anhui University,Hefei230601,China;2. School of Business, Anhui University,Hefei230601,China)

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    摘要:

    针对图像椒盐噪声,提出基于加权超图和诱导有序加权平均(IOWA)算子的椒盐噪声滤除算法.首先,用加权超图对图像进行表示,根据椒盐噪声为极值的特点,定义超图边的权值,该权值能够反映边内中心节点对应像素为噪声点的可能性,进而利用超图边的权值进行噪声检测;其次,构建IOWA算子对噪声点进行复原,并采用噪声检测与复原交替进行的方式完成图像的椒盐噪声滤除.仿真实验结果表明,所提出的算法不但可有效复原椒盐噪声,而且能保持原图像的轮廓等细节信息.

    Abstract:

    Aiming to filter the salt and pepper noise, this paper proposes an algorithm for removal of the salt and pepper noise based on the weighted hypergraph and induced ordered weighted averaging(IOWA) operator. Firstly, a weighted hypergraph is proposed to represent an image. According to the fact that noisy pixels take either the maximum value or the minimum value, the edge weight of the hypergraph is constructed. This edge weight can reveal the possibility of the pixel corresponding to the center node of the edge being noise, so that it can be used to detect the noise in image. Then, the IOWA operator is built to restore the noise. The noise detecting and restoring is alternative to accomplish the denoising of the whole image. The simulated experiments demonstrate that the proposed method can not only remove the salt and pepper noise, but also keep the contour information and other detail information of the original image.

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徐沁,刘金培,汤进,等.基于加权超图和IOWA算子的图像椒盐噪声滤除算法[J].控制与决策,2017,32(4):637-641

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  • 在线发布日期: 2017-03-28
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