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中文摘要：
用加权网络对图像进行建模，可以有效地表示图像的结构特征，其中网络单个节点的点强度集成了节点本身与其它点连接的边数和强度信息。为了发挥结构信息和统计信息在图像分析中的作用，用加权网络对图像进行表示。根据噪声像素与周围像素差异性大的特点，将噪声检测问题转化为搜索网络中具有最小点强度的节点问题。采用有序加权平均（OWA）算子对噪声点周围像素提供的信息进行集成以滤除噪声像素。采取啭检测和滤除交替进行的方式，提出了一种新颖的图像椒盐噪声滤除算法。实验结果表明了此算法的有效性。
英文摘要：
Image modeling by weighted network can powerfully characterize the structure of images. The node strength of a single node in a weighted network integrates the information on the number and the weights of links incident in it. In order to make good use of structural and statistical information in image analysis,the image is represented by a weighted network. Normally, the dissimilarity between the salt and pepper noise pixel and its nearest neighbor pixels is significant. The noise detection problem has been transformed into a problem of finding the node which has the minimal node strength. An ordered weighted average （OWA） operator is adopted to integrate the information provided by the pixels encompassing the noise pixel for restoration. In this way,a novel algorithm for removing salt and pepper noise in images is developed, where the noise detecting procedure and the filtering procedure are interleaved. Experimental results demonstrate the effectiveness of the proposed algorithm.
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