基于灰色系统模型的图像椒盐噪声去除新方法

Tongli He, Jianhong Gan
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引用次数: 5

摘要

针对中值滤波方法去噪时图像细节丢失的问题,提出了一种基于灰色系统理论的椒盐噪声滤波算法。该算法采用先对当前像素进行排序再进行滤波的思路,将所有像素根据噪声特征分为两组,一组为可疑噪声,另一组为信号像素。对于可疑噪声,采用灰色系统模型对噪声进行滤波,对信号像素不做任何处理,以保留更多的图像细节。实验结果表明,与常用的中值滤波算法相比,该方法不仅具有更好的降噪性能,而且具有较强的细节保留能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new method of removing salt-and-pepper noise basing on grey system model in images
Focusing on the problem of image details losing while denoising image using Median filter method, the article proposes a salt and pepper noise filtering algorithm basing on grey system theory. The algorithm employs the idea of sorting out current pixel firstly and then filtering, where all the pixels are classified into two groups, according to the noise characteristics, one is suspicious noise and the other is signal pixel. For suspicious noises, the grey system model is adopted to filter noises, and there are nothing to be done for signal pixels in order to preserve more image details. The results of experimental show that the proposed method not only achieved better noise reduction properties, but also has strong ability to preserve details compared with the commonly used median filter algorithm.
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